Robotic manipulators in warehousing and logistics often face complex tasks that involve multiple steps, frequent task switching, and long-term dependencies. Inspired by the hierarchical structure of human motor control, this paper proposes a Hierarchical Reinforcement Learning (HRL) framework utilizing a multi-task goal-conditioned Decision Transformer (MTGC-DT). The high-level policy treats the Markov decision process as a sequence modeling task, allowing the agent to manage temporal dependencies. The low-level policy is made up of parameterized action primitives that handle physical execution. This design improves long-term reasoning and generalization. This method is evaluated on two common logistics manipulation tasks: sequential stacking and spatial sorting with sparse reward and low-quality dataset. The main contributions include introducing a HRL framework that integrates Decision Transformer (DT) with task and goal embeddings, along with a path-efficiency loss (PEL) correction and designing a parameterized, learnable primitive skill library for low-level control to enhance generalization and reusability. Experimental results demonstrate that the proposed Decision Transformer-based Hierarchical Reinforcement Learning (DT-HRL) achieves over a 10% higher success rate and over 8% average reward compared with the baseline, and a normalized score increase of over 2% in the ablation experiments.

Abstract

The English for Academic Purposes (EAP) is pivotal for scholarly communication; however, it poses significant challenges for non-native English speakers. Recently, Large Language Models (LLMs) have been extensively utilized in EAP to assist with writing tasks. EAP writing assistance typically encompasses several downstream tasks in natural language processing, such as Grammatical Error Correction (GEC). Nonetheless, some studies have revealed that the performance of LLMs in GEC tasks is inferior to traditional GEC solutions. To explore the capabilities of LLMs more thoroughly in aspects like deep semantic and syntactic structures, this study aims to rigorously assess the performance of LLMs in the Sentence-level Revision (SentRev) task. We designed three sets of meticulous experiments to evaluate the efficacy of different LLMs. The first experiment assessed LLMs using prompts in ten different languages, finding that the SentRev performance of LLMs was heavily influenced by the language of the prompt and the quality of the input text. The second experiment investigated the performance of English LLMs with minimal prompting in the SentRev task, yet the results showed no significant changes, contradicting some prior studies. In the third experiment, we devised an innovative and straightforward method that significantly enhanced the performance of multiple LLMs by integrating academic phrases from the Formulaic Language Academic Phrasebank ( https://www.phrasebank.manchester.ac.uk/ ), thus overcoming the performance limitations imposed by different languages on LLMs. Additionally, our study highlights the deficiencies in existing evaluation benchmarks and suggests that higher-level, discourse-based EAP text evaluation benchmarks merit deeper exploration.

In the realm of academic English writing, both native (L1) and non-native (L2) speakers face significant challenges due to the complex linguistic structures and conventions required. Existing writing assistance tools, while useful for grammar correction and text enhancement, often fall short by providing only corrected output without explanations, and they typically operate as opaque, proprietary systems. This study introduces AcademiCraft, a novel EAP writing assistance built upon a multi-agent system (MAS) and advanced large-language models (LLMs), integrating state-of-the-art natural language processing (NLP) and linguistic research. AcademiCraft distinguishes itself by correcting and refining academic texts and offering detailed explanations for its revisions, thereby deepening the user’s understanding of writing conventions. The tool’s open and replicable framework contrasts sharply with the closed nature of most commercial products. Through a series of rigorous scientific benchmarks, AcademiCraft has been shown to outperform leading commercial writing assistance tools in several key areas, including its ability to handle complex syntactic structures, improve coherence and cohesion in academic texts, and provide contextually accurate word choices, all while maintaining high levels of grammatical precision. This paper details the methodologies and underlying principles of AcademiCraft, and presents a comparative analysis of its performance, demonstrating its superior capability in supporting both L1 and L2 writers in mastering the complexities of academic English writing.

Human–Robot Interaction (HRI) using hand gesture recognition offers an effective and non-contact approach to enhancing operational intuitiveness and user convenience. However, most existing studies primarily focus on either static sign language recognition or the tracking of hand position and orientation in space. These approaches often prove inadequate for controlling complex robotic systems. This paper proposes an advanced HRI system leveraging dynamic hand gestures for controlling quadruped robots equipped with a robotic arm. The proposed system integrates both semantic and pose information from dynamic gestures to enable comprehensive control over the robot’s diverse functionalities. First, a Depth–MediaPipe framework is introduced to facilitate the precise three-dimensional (3D) coordinate extraction of 21 hand bone keypoints. Subsequently, a Semantic-Pose to Motion (SPM) model is developed to analyze and interpret both the pose and semantic aspects of hand gestures. This model translates the extracted 3D coordinate data into corresponding mechanical actions in real-time, encompassing quadruped robot locomotion, robotic arm end-effector tracking, and semantic-based command switching. Extensive real-world experiments demonstrate the proposed system’s effectiveness in achieving real-time interaction and precise control, underscoring its potential for enhancing the usability of complex robotic platforms.

In recent years, humanoid robot technology has been developing rapidly due to the need for robots to collaborate with humans or replace them in various tasks, requiring them to operate in complex human environments and placing high demands on their mobility. Developing humanoid robots with human-like walking and hopping abilities has become a key research focus, as these capabilities enable robots to move and perform tasks more efficiently in diverse and unpredictable environments, with significant applications in daily life, industrial operations, and disaster rescue. Currently, methods based on hybrid zero dynamics and reinforcement learning have been employed to enhance the walking and hopping capabilities of humanoid robots; however, model predictive control (MPC) presents two significant advantages: it can adapt to more complex task requirements and environmental conditions, and it allows for various walking and hopping patterns without extensive training and redesign. The objective of this study is to develop a bipedal robot controller using shooting method-based MPC to achieve human-like walking and hopping abilities, aiming to address the limitations of the existing methods and provide a new approach to enhancing robot mobility.

Walking robots have been widely applied in complex terrains due to their good terrain adaptability and trafficability. However, in some environments (such as disaster relief, field navigation, etc.), although a single strategy can adapt to various environments, it is unable to strike a balance between speed and stability. Existing control schemes like model predictive control (MPC) and traditional incremental control can manage certain environments. However, they often cannot balance speed and stability well. These methods usually rely on a single strategy and lack adaptability for dynamic adjustment to different terrains. To address this limitation, this paper proposes an innovative double-layer reinforcement learning algorithm. This algorithm combines Deep Double Q-Network (DDQN) and Proximal Policy Optimization (PPO), leveraging their complementary strengths to achieve both fast adaptation and high stability in complex terrains. This algorithm utilizes terrain information and the robot’s state as observations, determines the walking speed command of the quadruped robot Unitree Go1 through DDQN, and dynamically adjusts the current walking speed in complex terrains based on the robot action control system of PPO. The speed command serves as a crucial link between the robot’s perception and movement, guiding how fast the robot should walk depending on the environment and its internal state. By using DDQN, the algorithm ensures that the robot can set an appropriate speed based on what it observes, such as changes in terrain or obstacles. PPO then executes this speed, allowing the robot to navigate in real time over difficult or uneven surfaces, ensuring smooth and stable movement. Then, the proposed model is verified in detail in Isaac Gym. Wecompare the distances walked by the robot using six different control methods within 10 s. The experimental results indicate that the method proposed in this paper demonstrates excellent speed adjustment ability in complex terrains. On the designed test route, the quadruped robot Unitree Go1 can not only maintain a high walking speed but also maintain a high degree of stability when switching between different terrains. Ouralgorithm helps the robot walk 25.5 m in 10 s, outperforming other methods.

Estimating the 6D pose and size of objects is crucial in the task of visual grasping for robotic arms. Most current algorithms still require the 3D CAD model of the target object to match with the detected points, and they are unable to predict the object’s size, which significantly limits the generalizability of these methods. In this paper, we introduce category priors and extract high-dimensional abstract features from both the observed point cloud and the prior to predict the deformation matrix of the reconstructed point cloud and the dense correspondence between the reconstructed and observed point clouds. Furthermore, we propose a staged geometric correction and dense correspondence refinement mechanism to enhance the accuracy of regression. In addition, a novel lightweight attention module is introduced to further integrate the extracted features and identify potential correlations between the observed point cloud and the category prior. Ultimately, the object’s translation, rotation, and size are obtained by mapping the reconstructed point cloud to a normalized canonical coordinate system. Through extensive experiments, we demonstrate that our algorithm outperforms existing methods in terms of performance and accuracy on commonly used benchmarks for this type of problem. Additionally, we implement the algorithm in robotic arm-grasping simulations, further validating its effectiveness.

As technology rapidly evolves, the application of bipedal robots in various environments has widely expanded. These robots, compared to their wheeled counterparts, exhibit a greater degree of freedom and a higher complexity in control, making the challenge of maintaining balance and stability under changing wind speeds particularly intricate. Overcoming this challenge is critical as it enables bipedal robots to sustain more stable gaits during outdoor tasks, thereby increasing safety and enhancing operational efficiency in outdoor settings. To transcend the constraints of existing methodologies, this research introduces an adaptive bio-inspired exploration framework for bipedal robots facing wind disturbances, which is based on the Deep Deterministic Policy Gradient (DDPG) approach. This framework allows the robots to perceive their bodily states through wind force inputs and adaptively modify their exploration coefficients. Additionally, to address the convergence challenges posed by sparse rewards, this study incorporates Hindsight Experience Replay (HER) and a reward-reshaping strategy to provide safer and more effective training guidance for the agents. Simulation outcomes reveal that robots utilizing this advanced method can more swiftly explore behaviors that contribute to stability in complex conditions, and demonstrate improvements in training speed and walking distance over traditional DDPG algorithms.

There are many studies analyzing human motion. However, we do not yet fully understand the mechanisms of our own bodies. We believe that mimicking human motion and function using a robot will help us to deepen our understanding of humans. Therefore, we focus on the characteristics of the human gait, and the goal is to realize a human-like bipedal gait that lands on its heels and takes off from its toes. In this study, we focus on kinematic synergy (planar covariation) in the lower limbs as a characteristic gait seen in humans. Planar covariation is that elevation angles at the thigh, shank, and foot in the sagittal plane are plotted on one plane when the angular data are plotted on the three axes. We propose this feature as a reward for reinforcement learning. By introducing this reward, the bipedal robot achieved a human-like bipedal gait in which the robot lands on its heels and takes off from its toes. We also compared the learning results with those obtained when this feature was not used. The results suggest that planar covariation is one factor that characterizes a human-like gait.

Abstract

Biped robots with dynamic motion control have shown strong robustness in complex environments. However, many motion planning methods rely on models, which have difficulty dynamically modifying the walking cycle, height, and other gait parameters to cope with environmental changes. In this study, a heuristic model-free gait template planning method with dynamic motion control is proposed. The gait trajectory can be generated by inputting the desired speed, walking cycle, and support height without a model. Then, the stable walking of the biped robot can be realized by foothold adjustment and whole-body dynamics model control. The gait template can be changed in real time to achieve gait flexibility of the biped robot. Finally, the effectiveness of the method is verified by simulations and experiments of the biped robot BHR-B2. The research presented here helps improve the gait transition ability of biped robots in dynamic locomotion.

This paper proposes a system for stable ladder climbing of the human-sized four-limbed robot "WAREC-1", including the following 3 components: (a) Whole-body motion planning; (b) Rung recognition system and (c) Reaction force adjustment. These 3 components guarantee appropriate ladder climbing motion, successful rung grub and proper reaction force distribution at contact points throughout the climbing motion, respectively. With this system, (1) Stable ladder climbing in 2-point contact gait by a human-sized robot and (2) Successful and stable climbing of an irregular ladder (with a higher or inclined rung) in both 3-point and 2-point contact gait with the capability of recognizing the target rung and the corresponding motion planning are realized, which have rarely been realized by former studies. Finally, experiment results and data of the robot ladder climbing are also presented to evaluate the proposed system.

Herein, we have developed a humanoid robot that achieves dynamic motion. Focusing on the running motion that is the basis of the motion, the robot has been developed focusing on the pelvic rotation on the frontal plane and the elasticity in leg joints (that changes according to running speed), which are the characteristics of humans during running. However, the variable joint stiffness mechanism that we have developed was large and heavy. Therefore, to make the mechanism smaller and lighter, we shorten the length of the leaf spring. We succeeded in downsizing the mechanism by changing its rectangular shape to trapezoidal, while maintaining strength and elasticity. The variable joint stiffness mechanism thus developed was more flexible, and its weight was reduced from 1.9 kg to 0.7 kg. The mechanism was mounted on the ankle joint, and it was confirmed that the required specifications were satisfied.

We are developing the biped humanoid robot WATHLETE-1 (Waseda ATHLETE humanoid No.1) that has the same mass arrangement, link ratio, and output characteristics as humans. It is not possible to mount high-power electromagnetic motors and mechanical transmissions that satisfy the hip joint output at running because its weight makes it impossible to realize human body characteristics. To realize the characteristics of the human body, we adopted a hydraulic drive system that has a more advanced design than a mechanical transmission mechanism, that concentrates on the joints, and that can distribute output by splitting and merging oil. We propose a hydraulic circuit that improves the output of the actuator by connecting two hydraulic direct drive systems (HDDs) in parallel, independently mounted on the ankle and the hip joints using proportional valves. As a result, it has been confirmed that hip joint speed was improved by 200% compared to a single HDDs and with the potential of simulating the hip joint output required for a human running at 2.0 m/s.

Towards the actualization of autonomous switch operation method for the disaster response robot, it is necessary to estimate the position and orientation of the switch in the site. This paper proposes a method for estimating switch orientation information based on the RGB-D sensor information attached to the disaster response robot. The flow of the proposed method in this paper consists of the following three stages. (1) Acquisition of RGB-D information of the switch area using the detection result of YOLOv3. (2) Position estimation of switch operation part by CNN from RGB-D information of switch area. (3) Estimation of switch orientation information using switch operation part position information and information on wall plane on which the switch exists. In the experiment, the proposed method was applied to three types of switch boxes, and the calculation results of the orientation information were evaluated. It was found from the experimental results that the calculation with sufficient accuracy is possible.2020. Int. J. Mech. Eng. Rob. Res

To achieve one of the tasks required for disaster response robots, this paper proposes a method for locating 3D structured switches' points to be pressed by the robot in disaster sites using RGBD images acquired by Kinect sensor attached to our disaster response robot. Our method consists of the following five steps: 1)Obtain RGB and depth images using an RGB-D sensor. 2) Detect the bounding box of switch area from the RGB image using YOLOv3. 3)Generate 3D point cloud data of the target switch by combining the bounding box and the depth image.4)Detect the center position of the switch button from the RGB image in the bounding box using Convolutional Neural Network (CNN). 5)Estimate the center of the button's face in real space from the detection result in step 4) and the 3D point cloud data generated in step3) In the experiment, the proposed method is applied to two types of 3D structured switch boxes to evaluate the effectiveness. The results show that our proposed method can locate the switch button accurately enough for the robot operation.

This chapter introduces a novel four-limbed robot, WAREC-1, that has advanced locomotion and manipulation capability with versatile locomotion styles. At disaster sites, there are various types of environments through which a robot must traverse, such as rough terrain filled with rubbles, narrow places, stairs, and vertical ladders. WAREC-1 moves in hazardous environments by transitioning among various locomotion styles, such as bipedal/quadrupedal walking, crawling, and ladder climbing. WAREC-1 has identically structured limbs with 28 degrees of freedom (DoF) in total with 7-DoFs in each limb. The robot is 1,690 mm tall when standing on two limbs, and weighs 155 kg. We developed three types of actuator units with hollow structures to pass the wiring inside the joints of WAREC-1, which enables the robot to move on rubble piles by creeping on its stomach. Main contributions of our research are following five topics: (1) Development of a four-limbed robot, WAREC-1. (2) Simultaneous localization and mapping (SLAM) using laser range sensor array. (3) Teleoperation system using past image records to generate a third-person view. (4) High-power and low-energy hand. (5) Lightweight master system for telemanipulation and an assist control system for improving the maneuverability of master-slave systems.

In previous studies, various stabilizing control methods for humanoids during the stance phase while hopping and running were proposed. Although these methods contribute to stability while hopping and running, it is possibility that the control during the flight phase could also affect the stability. In this study, we investigated whether the control during the flight phase can affect the stability of a humanoid while running. To achieve stable hopping, we developed a control system that accounts for the angular momentum of the whole body during the flight phase. In this system, the angular momentum generated by the motion of the lower body in each time interval is calculated during the flight phase, and the trunk joints are controlled to generate the angular momentum necessary to compensate for the deviation of the waist posture, which is used as the reference point for the motion coordinate system of the robot. Once the proposed control system was developed and simulated, we found that the hopping duration in the unconstrained state was extended.

While running, humans use the stiffness of the knee and ankle joint of the leg. Mimicking this motion can improve the output power and performance of humanoid robots. It also offers the possibility of clarifying running in humans, from an engineering perspective, by mimicking other characteristics of an ankle joint. In this paper, we design an ankle and foot mechanism that mimics human’s characteristics, such as joint stiffness in the direction of pitch, and following the floor surface in the direction of roll upon landing for stabilization. To mimic these characteristics, our ankle joint mechanism consisted of CFRP (Carbon Fiber Reinforced Plastic)-laminated leaf springs implemented on the foot of the robot for a deflection in direction of pitch and a twist in the direction of the roll. We ensured that the ankle joint can follow the ground in the direction of roll at landing in a hopping experiment.

Many extant studies proposed various stabilizing control methods for humanoids during the stance phase while hopping and running. Although these methods contribute to stability during hopping and running, humanoid robots do not swing their legs rapidly during the flight phase to prevent rotation in the yaw direction. Humans utilize their torsos and arms when running to compensate for the angular momentum in the yaw direction generated by leg movement during the flight phase. In this study, we developed an angular momentum control method based on human motion for a humanoid upper body. The method involves calculation of the angular momentum generated by the movement of the humanoid legs and calculation of the torso and arm motions required to compensate for the angular momentum of the legs in the yaw direction. We also developed a humanoid upper-body mechanism having human link length and mass properties, using carbon-fiber-reinforced plastic and a symmetric structure for generating large angular momentum. The humanoid robot developed in this study could generate almost the same angular momentum as that of a human. Furthermore, when suspended in midair, the humanoid robot achieved angular momentum compensation in the yaw direction.

Trajectory optimization and posture generation are hard problems in robot locomotion, which can be nonconvex and have multiple local optima. Progress on these problems is further hindered by a lack of open benchmarks, since comparisons of different solutions are difficult to make. In this paper we introduce a new benchmark for trajectory optimization and posture generation of legged robots, using a pre-defined scenario, robot and constraints, as well as evaluation criteria. We evaluate state-of-The-Art trajectory optimization algorithms based on sequential quadratic programming (SQP) on the benchmark, as well as new stochastic and incremental optimization methods borrowed from the large-scale machine learning literature. Interestingly we show that some of these stochastic and incremental methods, which are based on stochastic gradient descent (SGD), achieve higher success rates than SQP on tough initializations. Inspired by this observation we also propose a new incremental variant of SQP which updates only a random subset of the costs and constraints at each iteration. The algorithm is the best performing in both success rate and convergence speed, improving over SQP by up to 30% in both criteria. The benchmark's resources and a solution evaluation script are made openly available.

This paper describes an approach that enables the four-limbed robot 'WAREC-1' to climb up and down vertical ladders stably. First, the four-limbed robot 'WAREC-1' is introduced and dynamic stability conditions in multi-mass model for ladder climbing are proposed as the basis of judging whether a four-limbed robot is stable or not while climbing a vertical ladder. According to the proposed stability conditions, 3 different types of moment will directly affect the stability of the robot on a ladder: gravitational moment, inertial moment and reaction force moment. With the analysis of these 3 kinds of moments and the relationship among them, stability control methods are proposed to maintain stability of the robot on a ladder to the greatest degree and avoid their mutual interference. Combining with the stability conditions and stability control proposed, stable motion planning of climbing up and down a vertical ladder, a motion planning method proposed by the authors that allows independent path and time planning in trajectory planning is also applied to reinforce the efficiency of the stability control. Eventually, results from the simulation and physical robot verify the validity of the proposed control methods.

This paper describes a novel four-limbed robot having high mobility capability in extreme environments. At disaster sites, there are various types of environments where a robot must move such as rough terrain with possibility of collapse, narrow places, stairs, vertical ladders and so forth. In this paper, first we categorized extreme environments based on three indexes: unevenness, narrowness, and inclination. To move in such extreme environments, we proposed a four-limbed robot having various locomotion styles such as bipedal/quadrupedal walking, crawling and ladder climbing. The main contribution of this paper is the concept and hardware design of the four-limbed robot. We developed a prototype of the four-limbed robot having commonly structured limbs. The number of DoF for the whole body is 29, with 7-DoFs in each limb and 1-DoF in the trunk. The robot weight is 110 kg, and the height is 1,290 mm when standing on two legs. The end-effector has hook-like shape. Verification of the prototype robot is conducted through simulations and experiments.

This paper presents a novel four-limbed robot, WAREC-1 having high locomotion ability with versatility in locomotion styles. At disaster sites, there are various types of environments where a robot must move such as rough terrain with possibility of collapse, narrow places, stairs, vertical ladders and so on. WAREC-1 moves in hazardous environments by changing locomotion styles: Bipedal/quadrupedal walking, crawling, and ladder climbing. WAREC-1 has commonly structured limbs with 28-DoFs in total with 7-DoFs in each limb. The robot is 1,690 mm tall when standing on two limbs and weighs 155 kg. We developed three types actuator units with hollow structure to pass the wiring inside the joints of WAREC-1, which enables the robot to move on rubble by creeping on its stomach. The body has a concave shape, and the end-effector has hook-like shape. Verification of the WAREC-1 robot is conducted through experiments.

In this paper, we describe a gait generation method for the crawling motion of a legged robot using Normalized Energy Stability Margin (NESM). The crawling motion is a method of locomotion that, since the robot is very close to a state of falling, its leg and torso are grounded alternately in order to enable the robot to move with a low center of gravity. It has the benefit of decreasing the impact experienced by the robot and reduces the risk of becoming damaged if it falls over. However, during the phase where only the robot's torso is in contact with the ground, the size of robot's support area is smaller than the case when its legs are in contact with the ground. This decrease in support area may cause the robot to fall or tip over sideways in the direction where the edge of robot's cuboid torso is providing the most support on an inclined surface. As a result, the robot's feet may collide with the road's surface when its legs are moving forward and prevent the robot from performing its crawling motion. To deal with this problem, we propose a method of gait generation for the crawling motion based on a stability criteria. Depending on the stability criteria, this method involves the selection of a stance, with which it lifts its torso and a way of controlling the landing height of the robot's feet depending on the unevenness of the surface of the road. In experiments, it has been confirmed that stability was improved when the four-limbed robot performed the crawling motion using the proposed method on an inclined road surface.

In this paper, we propose a crawling motion to reduce the risk of malfunction due to falling when a legged robot travels across rough terrain. This locomotion method includes a phase in which the torso of the robot comes into contact with the ground to lower its center of mass compared with that during conventional bipedal or quadrupedal walking motion. In rough terrain, the ability of a robot to crawl is very likely to be hindered since its feet may encounter holes or protrusions caused by road surface damage. To avoid this issue, we suggest a modified foot trajectory control method based on information obtained by force and attitude angle sensors. To verify the effectiveness of the proposed crawling motion on rough terrain, we created a terrain model using a dynamics simulator and conducted an experiment by applying the proposed control method to a four-limbed robot traveling across the modelled terrain. The experimental results confirmed that a robot can successfully traverse rough terrain using the proposed crawling motion and that the foot trajectory modification control method can enhance the performance of the robot during such motion.

Humans utilize their torsos and arms while running to compensate for the angular momentum generated by the lower-body movement during the flight phase. To enable this capability in a humanoid robot, the robot should have human-like mass, a center of mass position, and inertial moment of each link. To mimic this characteristic, we developed an angular momentum control method using a humanoid upper body based on human motion. In this method, the angular momentum generated by the movement of the humanoid lower body is calculated, and the torso and arm motions are calculated to compensate for the angular momentum of the lower body. We additionally developed the humanoid upper-body mechanism that mimics the human link length and mass property by using carbon fiber reinforced plastic and a symmetric structure. As a result, the developed humanoid robot could generate almost the same angular momentum as that of human through human-like running motion. Furthermore, when suspended in midair, the humanoid robot produced the angular momentum compensation in the yaw direction.

Neuroscientific studies show that humans tend to stabilize their head orientation, while accomplishing a locomotor task. This is beneficial to image stabilization and in general to keep a reference frame for the body. In robotics, too, head stabilization during robot walking provides advantages in robot vision and gaze-guided locomotion. In order to obtain the head movement behaviors found in human walk, it is necessary and sufficient to be able to control the orientation (roll, pitch and yaw) of the head in space. Based on these principles, three controllers have been designed. We developed two classic robotic controllers, an inverse kinematics based controller, an inverse kinematics differential controller and a bio-inspired adaptive controller based on feedback error learning. The controllers use the inertial feedback from a IMU sensor and control neck joints in order to align the head orientation with the global orientation reference. We present the results for the head stabilization controllers, on two sets of experiments, validating the robustness of the proposed control methods. In particular, we focus our analysis on the effectiveness of the bio-inspired adaptive controller against the classic robotic controllers. The first set of experiments, tested on a simulated robot, focused on the controllers response to a set of disturbance frequencies and a step function. The other set of experiments were carried out on the SABIAN robot, where these controllers were implemented in conjunction with a model of the vestibulo-ocular reflex (VOR) and opto-kinetic reflex (OKR). Such a setup permits to compare the performances of the considered head stabilization controllers in conditions which mimic the human stabilization mechanisms composed of the joint effect of VOR, OKR and stabilization of the head. The results show that the bio-inspired adaptive controller is more beneficial for the stabilization of the head in tasks involving a sinusoidal torso disturbance, and it shows comparable performances to the inverse kinematics controller in case of the step response and the locomotion experiments conducted on the real robot.

<p>This paper proposes a novel motor cooling method using direct-liquid cooling by immersing a heat source directly into coolant. Direct-liquid cooling is more effective than air cooling and indirect-liquid cooling because a heat source and coolant are in direct contact with each other. Further, if the shape of the shaft is designed to be able to perform heat transfer by forcibly circulating the coolant by the rotation of the motor itself, it will be possible to prevent the actuator unit from being enlarged.</p>

Energy efficiency and robustness of locomotion to different terrain conditions are important problems for humanoid robots deployed in the real world. In this paper, we propose a footstep-planning algorithm for humanoids that is applicable to flat, slanted, and slippery terrain, which uses simple principles and representations gathered from human gait literature. The planner optimizes a center-of-mass (COM) mechanical work model subject to motion feasibility and ground friction constraints using a hybrid A*search and optimization approach. Footstep placements and orientations are discrete states searched with an A*algorithm, while other relevant parameters are computed through continuous optimization on state transitions. These parameters are also inspired by human gait literature and include footstep timing (double-support and swing time) and parameterized COM motion using knee flexion angle keypoints. The planner relies on work, the required coefficient of friction (RCOF), and feasibility models that we estimate in a physics simulation. We show through simulation experiments that the proposed planner leads to both low electrical energy consumption and human-like motion on a variety of scenarios. Using the planner, the robot automatically opts between avoiding or (slowly) traversing slippery patches depending on their size and friction, and it chooses energy-optimal stairs and climbing angles in slopes. The obtained motion is also consistent with observations found in human gait literature, such as human-like changes in RCOF, step length and double-support time on slippery terrain, and human-like curved walking on steep slopes. Finally, we compare COM work minimization with other choices of the objective function.

This letter describes the development of a humanoid arm with quick-and-wide motion capability for making humans laugh. Laughter is attracting research attention because it enhances health by treating or preventing mental diseases. However, laughter has not been used effectively in healthcare because the mechanism of laughter is complicated and is yet to be fully understood. The development of a robot capable of making humans laugh will clarify the mechanism how humans experience humor from stimuli. Nonverbal funny expressions have the potential to make humans laugh across cultural and linguistic differences. In particular, we focused on the exaggerated arm motion widely used in slapsticks and silent comedy films. In order to develop a humanoid robot that can perform this type of movement, the required specification was calculated from slapstick skits performed by human comedians. To meet the required specifications, new arms for the humanoid robot were developed with a novel mechanism that includes lightweight joints driven by a flexible shaft and joints with high output power driven by a twin-motor mechanism. The results of experimental evaluation show that the quick-and-wide motion performed by the developed hardware is effective at making humans laugh.

We propose a novel heel-contact toe-off walking pattern generator for a biped humanoid robot. It is divided in two stages: a simple model stage where a Linear Inverted Pendulum (LIP) based heel-contact toe-off walking model based on the so-called functional rockers of the foot (heel, ankle and forefoot rockers) is used to calculate step positions and timings, and the Center of Mass (CoM) trajectory taking step lengths as inputs, and a multibody dynamics model stage, where the final pattern to implement on the humanoid robot is obtained from the output of the first simple model stage. The final pattern comprises the Zero Moment Point (ZMP) reference, the joint angle references and the end effector references. The generated patterns were implemented on our robotic platform, WABIAN-2R to evaluate the generated walking patterns.

A biped humanoid robot is prone to fall when walking or operating in a complex environment, and forward fall is one of the most common falling cases. This study focuses on the forward fall issue and presents an"Arm Flexible Landing Strategy" for safe falling. First, the forward falling motion is analyzed from an energy variation perspective of the robot system, and a method to choose best-fit landing attitude of the arm is presented. Then, a exible landing controller is implemented in the arm to reduce the impact force to the robot, thereby further increasing protection. The presented algorithm is very easy to implement and does not require any additional physical elements to the robot. Finally, a series of simulations are made on a humanoid robot to validate the effectiveness of the presented methods on a safe landing.

In this paper we tackle the problem of visually predicting surface friction for environments with diverse surfaces, and integrating this knowledge into biped robot locomotion planning. The problem is essential for autonomous robot locomotion since diverse surfaces with varying friction abound in the real world, from wood to ceramic tiles, grass or ice, which may cause difficulties or huge energy costs for robot locomotion if not considered. We propose to estimate friction and its uncertainty from visual estimation of material classes using convolutional neural networks, together with probability distribution functions of friction associated with each material. We then robustly integrate the friction predictions into a hierarchical (footstep and full-body) planning method using chance constraints, and optimize the same trajectory costs at both levels of the planning method for consistency. Our solution achieves fully autonomous perception and locomotion on slippery terrain, which considers not only friction and its uncertainty, but also collision, stability and trajectory cost. We show promising friction prediction results in real pictures of outdoor scenarios, and planning experiments on a real robot facing surfaces with different friction.

Friction estimation from vision is an important problem for robot locomotion through contact. The problem is challenging due to its dependence on many factors such as material, surface conditions and contact area.
In this paper we 1) conduct an analysis of image features that correlate with humans' friction judgements; and 2) compare algorithmic to human performance at the task of predicting the coefficient of friction between different surfaces and a robot's foot. The analysis is based on two new datasets which we make publicly available. One is annotated with human judgements of friction, illumination, material and texture; the other is annotated with static coefficient of friction (COF) of a robot's foot and human judgements of friction. We propose and evaluate visual friction prediction methods based on image features, material class and text mining. And finally, we make conclusions regarding the robustness to COF uncertainty which is necessary by control and planning algorithms; the low performance of humans at the task when compared to simple predictors based on material label; and the promising use of text mining to estimate friction from vision.

Crawling motion by a robot is effective for reducing shock in the case of a fall. It thus decreases the possibility of a locomotion malfunction on uneven terrain. In this paper, the control of crawling motion on uneven terrain is described. Firstly, crawling motion and detailed motion are explained. Then, a method for controlling crawling motion is outlined for its realization. To verify the effectiveness of the proposed method for locomotion on uneven terrain, rough rubble ground was generated in a dynamics simulator and the crawling method was applied to our developed four-limbed robot. Additionally, a crawler robot was generated. A comparison was conducted to verify the difference in locomotion capabilities between the proposed method and other locomotion styles. The simulation results confirmed that the proposed method enabled successful locomotion of our four-limbed robot on uneven terrain.

This paper introduces a motion planning method to generate ladder climbing motion for a four-limbed robot. This method contains the following points: (1) independent planning of path and time in 3 dimensional space for trajectory planning; (2) path length minimization according to given midpoints. In trajectory planning, arc-length parameterization is used to separate path planning and time planning so that they can be done independently. After path is planned, time planning along the planned path can be given freely to meet our requirement, such as speed and acceleration adjustment for the protection of motors, optimization for dynamics analysis, dynamic obstacle avoidance and so on. Results from simulations and experiments authenticate the validity of our motion generation method.

This paper describes the development of one DoF robotic hand that makes human laugh by tickling through rubbing underarm. Laughter is attracting research attention because it enhances health by treating or preventing mental diseases. However, laughter has not been used effectively in healthcare because the mechanism of laughter is complicated and is yet to be fully understood. The development of a robot capable of making humans laugh is useful for clarifying the mechanism of laughter because the stimuli by the robot is quantitative and reproductive. Especially, tickling matches to this purpose because the relationship between stimuli and reaction is simpler compared to other techniques. Therefore, this research aimed to develop a robotic hand that can output quantitative and reproductive tickling stimuli for clarifying the mechanism of laughter. Rubbing underarm is selected as a target motion of robot because previous research suggested that this is the best way for making humans feel ticklish. In order to achieve the tickling motion by robots as humans, the required specifications were determined through experimental method. In order to develop a robot that achieves the required fingertip trajectory by simple mechanisms as much as possible, mechanism with crank and link driven by single motor was developed. The result of experimental evaluation shows that the developed robot could make humans laugh by its rubbing motion. In addition, the quantitative tickling motion by developed robotic hand was suggested to be effective for clarifying the mechanism of laughter.

Cats have protractible claws to fold their tips to keep them sharp. They protract claws while hunting and pawing on slippery surfaces. Protracted claws by tendons and muscles of toes can help cats anchoring themselves steady while their locomotion trends to slip and releasing the hold while they retract claws intentionally. This research proposes a kind of modularized self-adaptive toe mechanism inspired by cat claws to improve the extremities' contact performance for legged robot. The mechanism is constructed with four-bar linkage actuated by contact reaction force and retracted by applied spring tension. A feasible mechanical design based on several essential parameters is introduced and an integrated Sole-Toe prototype is built for experimental evaluation. Mechanical self-adaption and actual contact performance on specific surface have been evaluated respectively on a biped walking platform and a bench-top mechanical testing.

This paper describes a trajectory planning method of ladder climbing for a four-limbed robot. The overall design of the four-limbed robot and the specific design of its end-effector is explained. The trajectory planning consists of two components: path planning and time planning, and the separation of these two parts are realized by arc-length parameterization. In path planning, we use cubic spline interpolation to generate the path according to the given mid-points. It is a fact that the shape of path depends on the choice of the coefficients of the interpolation polynomial, and so does the path length. Therefore, we propose a minimization of path length so that once the mid-points are all given, the generated path will always be the shortest spline curve. For time planning, it enables us to decide how long the path goes in arbitrary given times. Due to the independence between path and time planning, different time planning along the same path can be applied for the purpose of speed adjustment, avoidance of moving obstacles, releasing the burden of motors and so on. Results from simulations and experiments authenticate the validity of our trajectory planning method.

Human steady running is modeled using a spring-loaded inverted pendulum ( SLIP). However, human pushes off the ground actively when starting to run. In this study, we describe a knee joint mechanism for coping with both of an active pushing-off and joint stiffness needed to continue running. To achieve this, knee is equipped with a mechanism comprising a worm gear that improves torque transmission efficiency in order to achieve active movement and two laminated leaf springs for mimicking joint stiffness. We evaluated the performance of the laminated leaf spring and performed an experiment in which the developed running robot started to run. Using the proposed mechanisms, this robot could accomplish hopping with an active pushing-off motion and continued to run using its joint elasticity.

This paper describes the development of end-effector for disaster response robot with commonly structured limbs and experiment of climbing a vertical ladder. The end-effector is required to have the ability to hang on rungs and side rails and work as both hands and feet. We developed an end-effector with hook-like shape so that it can hang on both rungs and side rails, and grooves on the back of hook make it possible for the end-effector to play the role of both hands and feet, fixing on the rungs of ladder firmly. Moreover, the design of the end-effector allows the robot to perform some locomotion style other than climbing, like bipedal walking. We made the experiment in climbing a ladder obeying Japanese Industrial Standards (JIS) performed by the robot. As a result, end-effectors enabled the robot's feet to reach the highest rung.

This paper describes the mechanism and control of a disturbance force generator that is able to evaluate disturbance compensation control of biped robots quantitatively. The disturbance generator consists of a base, a motor drive system and a suspension system. In order to apply a disturbance force to a biped humanoid robot, a wire wound on a pulley of the disturbance generator is connected with robot's waist. The effectiveness of the disturbance force generator is verified through several disturbance experiments.

We developed a four-arm four-crawler advanced disaster response robot called OCTOPUS. Disaster response robots are expected to be capable of both mobility, e.g., entering narrow spaces over very rough unstable ground, and workability, e.g., conducting complex debris-demolition work. However, conventional disaster response robots are specialized in either mobility or workability. Moreover, strategies to independently enhance the capability of crawlers for mobility and arms for workability will increase the robot size and weight. To balance environmental applicability with the mobility and workability, OCTOPUS is equipped with a mutual complementary strategy between its arms and crawlers. The four arms conduct complex tasks while ensuring stabilization when climbing steps. The four crawlers translate rough terrain while avoiding toppling over when conducting demolition work. OCTOPUS is hydraulic driven and teleoperated by two operators. To evaluate the performance of OCTOPUS, we conducted preliminary experiments involving climbing high steps and removing attached objects by using the four arms. The results showed that OCTOPUS completed the two tasks by adequately coordinating its four arms and four crawlers and improvement in operability needs.

Stereo confidence measures are important functions for global reconstruction methods and some applications of stereo. In this article we evaluate and compare several models of confidence which are defined at the whole disparity range. We propose a new stereo confidence measure to which we call the Histogram Sensor Model (HSM), and show how it is one of the best performing functions overall. We also introduce, for parametric models, a systematic method for estimating their parameters which is shown to lead to better performance when compared to parameters as computed in previous literature. All models were evaluated when applied to two different cost functions at different window sizes and model parameters. Contrary to previous stereo confidence measure benchmark literature, we evaluate the models with criteria important not only to winner-take-all stereo, but also to global applications. To this end, we evaluate the models on a real-world application using a recent formulation of 3D reconstruction through occupancy grids which integrates stereo confidence at all disparities. We obtain and discuss our results on both indoors' and outdoors' publicly available datasets.

In this paper we use an extended footstep planning algorithm to plan optimal humanoid locomotion trajectories subject to constraints on the maximum predicted Zero Moment Point (ZMP) tracking error. The approach can guarantee walking stability bounds with little extra computational burden, thus increasing safety of robots walking in challenging environments. This is done by estimating energy and stability models in simulation through Bayesian optimization, and smartly integrating the models into search-based planning.

This paper explains a motion planning strategy that is not based on time but on "event", which can be explained as the path that the end-effector of robot tracks in our study. Arc-length parameterization is used in this paper to convert a time-based planning into an event-based planning. With our planning, it is possible to choose various time planning on the same given path so that tasks such as dynamic obstacle avoidance and performance test of motors become available. Simulation results about time planning implemented to a given path verifies the effectiveness of our event-based planning.

This paper describes the development of a four-limbed robot capable of climbing vertical ladders. We focused on vertical ladders which are often set in plant facilities. The design concepts and required specifications are explained. We conducted experiments of climbing vertical ladders and the robot succeeded in climbing vertical ladders in JIS.

Bipedal Walking Robot uses harmonic gears in its leg joints in order to provide high torque. However, those mechanisms increase the leg's weight that automatically increases the required energy. Replacing the drivable gear system with an adjustable stiffness mechanism might help to increase the energy efficiency. In this research we purpose a novel adjustable stiffness mechanism that can be attached to the ankle joint. The developed mechanism can provide passive and active controlled motion, which might help the robot to walk with less energy.

The running trajectory for bipedal robot is generated using numerically calculation method. Such method might limit the robot performance to accurately control its forward velocity. A new method is developed to determine the running trajectory based on linear equation that is developed based on walking trajectory and vertical hopping motion trajectory equations.

The unique "Tokku" Special Zone for Robot-ics Empirical Testing and Development (RT special zone) originated in Japan. Since 2003, the world's first RT special zone had already established in Fukuoka Prefecture, Fukuoka City and Kitakyushu City. At that time, Takanishi Laboratory, Humanoid Robotics Institute of Waseda University had conducted many empirical testing within several different spots of the special zone to evaluate the feasibility for bipedal humanoid robots on public roads from 2004 to 2007. It is also known as the world's first public roads testing for bipedal robots. The history of RT special zone is merely 10 years long, but there are already many special zones established in Fukuoka, Osaka, Gifu, Kanagawa and Tsukuba. As the development of robotics and its submergence to the society expand, the importance of RT special zone as an interface for robots and society will be more apparent. In this paper, our main focus is to view the impacts of the "Tokku" special zone system to the human-robot co-existence society. We would like to make a systematic review for RT special zone, and further to investigate the relationship between RT special zone, robots and the law through a case study on legal impacts regarding bipedal humanoid robots in which the materials for the case study come from Waseda University's experiment on WL-16RII and WABIAN-2R at the Fukuoka RT special zone.

The spring loaded inverted pendulum is used to model human running. It is based on a characteristic feature of human running, in which the linear-spring-like motion of the standing leg is produced by the joint stiffness of the knee and ankle. Although this model is widely used in robotics, it does not include human-like pelvic motion. In this study, we show that the pelvis actually contributes to the increase in jumping force and absorption of landing impact. On the basis of this finding, we propose a new model, spring loaded inverted pendulum with pelvis, to improve running in humanoid robots. The model is composed of a body mass, a pelvis, and leg springs, and, it can control its springs while running by use of pelvic movement in the frontal plane. To achieve running motions, we developed a running control system that includes a pelvic oscillation controller to attain control over jumping power and a landing placement controller to adjust the running speed. We also developed a new running robot by using the SLIP 2 model and performed hopping and running experiments to evaluate the model. The developed robot could accomplish hopping motions only by pelvic movement. The results also established that the difference between the pelvic rotational phase and the oscillation phase of the vertical mass displacement affects the jumping force. In addition, the robot demonstrated the ability to run with a foot placement controller depending on the reference running speed.

The Uncanny valley hypothesis, which tells us that almost-human characteristics in a robot or a device could cause uneasiness in human observers, is an important research theme in the Human Robot Interaction (HRI) field. Yet, that phenomenon is still not well-understood. Many have investigated the external design of humanoid robot faces and bodies but only a few studies have focused on the influence of robot movements on our perception and feelings of the Uncanny valley. Moreover, no research has investigated the possible relation between our uneasiness feeling and whether or not we would accept robots having a job in an office, a hospital or elsewhere. To better understand the Uncanny valley, we explore several factors which might have an influence on our perception of robots, be it related to the subjects, such as culture or attitude toward robots, or related to the robot such as emotions and emotional intensity displayed in its motion. We asked 69 subjects (N = 69) to rate the motions of a humanoid robot (Perceived Humanity, Eeriness, and Attractiveness) and state where they would rather see the robot performing a task. Our results suggest that, among the factors we chose to test, the attitude toward robots is the main influence on the perception of the robot related to the Uncanny valley. Robot occupation acceptability was affected only by Attractiveness, mitigating any Uncanny valley effect. We discuss the implications of these findings for the Uncanny valley and the acceptability of a robotic worker in our society.

An online walking pattern generation is important for a biped humanoid robot to move in dynamic environments. This chapter describes a novel online walking pattern generation using Fast Fourier Transform (FFT). Most previous studies about online walking pattern generation use an inverted pendulum model, which requires other methods to compensate for errors between the model and a real robot. Because our method uses a multi-body robot model, a biped robot can dynamically change its motions online by utilizing only the proposed method. If a robot has external sensors such as a stereo vision system to recognize dynamic environments, the robot can follow a moving target. Verification of the proposed method is conducted through experiments with the human-sized humanoid robots WABIAN-2R and KOBIAN.

Humanoid robot is anticipated to serve people in our daily life in the near future. However, the great cost of falling damage needs to be addressed before it is widely used. In this paper, a safe and compact joint with torque limiter is developed to reduce the damage to a humanoid robot during falling. First, the overall scheme design and working principles of the safe joint are investigated. Then, the mechanical design of the safe joint is presented in details. Finally, the effectiveness of the safe joint is verified by several simulations.

Energy consumption and stability are two important problems for humanoid robots deployed in remote outdoor locations. In this paper we propose an extended footstep planning method to optimize energy consumption while considering motion feasibility and ground friction constraints. To do this we estimate models of energy, feasibility and slippage in physics simulation, and integrate them into a hybrid A* search and optimization-based planner. The graph search is done in footstep position space, while timing (leg swing and double support times) and COM motion (parameterized height trajectory) are obtained by solving an optimization problem at each node. We conducted experiments to validate the obtained energy model on the real robot, as well as planning experiments showing 9 to 19% energy savings. In example scenarios, the robot can correctly plan to optimally traverse slippery patches or avoid them depending on their size and friction; and uses stairs with the most beneficial dimensions in terms of energy consumption.

This paper presents results of experimental investigation of the falling down of human body in order to identify significant characteristics and parameters that help for safe similar situations with humanoid robots. Experiments are discussed with results from lab tests that give both behavior and values of the biomechanics of falling down of human body. Simulations of humanoid robot falling verified the strategies concluded from the human falling down.

A complex relationship exists between people's cultural background and their general acceptance towards robots. Previous studies supported the idea that humans may accept more easily a robot that can adapt to their specific culture. However, it is not clear whether between two robots which are identified as foreign robots because of their verbal and non-verbal expressions, the one that is culturally closer may be preferred or not. In this experiment, participants of Dutch nationality were engaged in a simulated video conference with a robot that is greeting and speaking either in German or in Japanese; they completed a questionnaire assessing their preferences and their emotional state. As Dutch participant showed less signs of discomfort and better acceptance when interacting with a German robot, the hypothesis that acceptance of a robot could be directly proportional to cultural closeness was supported, while the hypothesis that similar foreign robots are equally less accepted regardless of the country-was rejected. Implications are discussed for how robots should be designed to be employed in different countries.

Human running motion can be modeled using a spring-loaded inverted pendulum (SLIP), where the linear-spring-like motion of the standing leg is produced by the joint stiffness of the knee and ankle. To use running speed control in the SLIP model, we should only decide the landing placement of the leg. However, for using running speed control with a multi-joint leg, we should also decide the joint angle and joint stiffness of the standing leg because these affect the direction of the ground reaction force. In this study, we develop a running control method for a human-like multi-joint leg. To achieve a running motion, we developed a running control method including pelvis oscillation control for attaining jumping power with the joint stiffness of the leg and running speed control by changing the landing placement of the leg. For using running speed control, we estimated the ground reaction force using the equation of motion and detected the joint angles of the leg for directing the ground reaction force toward the center of mass. To evaluate the proposed control methods, we compared the estimated ground reaction force with the force measured by the real robot. Moreover, we performed a running experiment with the developed running robot. By using ground reaction force estimation, this robot could accomplish the running motion with pelvic oscillation for attaining jumping power and running speed control.

Analysis of human running has revealed that the motion of the human leg can be modeled by a compression spring because the leg's joints behave like a torsion spring in the stance phase. Moreover, the knee bends rapidly to avoid contact of the foot with the ground in the swing phase. In this paper, we describe the development of a knee joint mechanism that mimics the elastic characteristics of the stance leg and rapid bending knee of the idling leg of a running human. The knee was equipped with a mechanism comprising two leaf springs and a worm gear for adjusting the joint stiffness and high-speed bending knee. Using this mechanism, we were able to achieve joint stiffness within the range of human knee joints that could be adjusted by varying the effective length of one of the leaf springs. In addition, the mechanism was able to bend rapidly by changing the angle between the two leaf springs. The equation proposed for calculating the joint stiffness considers the difference between the position of the fixed point of the leaf spring and the position of the rotational center of the joint. We evaluated the performance of the adjustable joint stiffness and the effectiveness of the proposed equation for joint stiffness and high-speed knee bending. We were able to make a bipedal robot hop using pelvic oscillation for storing energy produced by the resonance to leg elasticity and confirmed the mechanism could produce large torque 210 Nm.

Waseda University has researched on biped robots since 1967. This paper describes our latest biped robots: (i) WABIAN-2, (ii) a biped running robot, and (iii) WL-16. WABIAN-2 is a biped humanoid robot and has realized a human-like walk with the knees stretched by utilizing a 2-DOF waist mimicking a human's pelvis motion. We are developing a new biped humanoid robot which can jump by utilizing a pelvic movement and leg elasticity. WL-16 is a human-carrying biped vehicle.

We propose a new heel-contact toe-off walking model based on the Linear Inverted Pendulum (LIP) model, which due to the linearity and the ease of manipulation of the equations, could be considered to be advantageous for a future online implementation for the generation of walking patterns. This new model is based on the so called functional rockers of the foot (heel, ankle and forefoot rockers), each of which are modeled as an inverted pendulum, changing the ground contact point position of the inverted pendulums for each rocker. We focus on the motion of the Center of Mass (CoM) in the sagittal plane, as it is the plane on which the rockers take place, but also generate the motions on the frontal plane. The model proved to work for constant velocity, accelerating and decelerating gaits, and the effects of the change of pivot point during heel-contact toe-off could be corroborated in the Zero Moment Point (ZMP) graphs. The implementation of this model could improve the human likeness of the motions, as well as the stability of the locomotion.

Humanoid robots are expected to play a major role in the future of space and planetary exploration. Humanoid robot features could have many advantages, such as interacting with astronauts and the ability to perform human tasks. However, the challenge of developing such a robot is quite high due to many difficulties. One of the main difficulties is the difference in gravity. Most researchers in the field of bipedal locomotion have not paid much attention to the effect of gravity. Gravity is an important parameter in generating a bipedal locomotion trajectory. This research investigates the effect of gravity on bipedal walking motion. It focuses on low gravity, since most of the known planets and moons have lower gravity than earth. Further study is conducted on a full humanoid robot model walking subject to the moon's gravity, and an approach for dealing with moon gravity is proposed in this paper.

We describe a learning strategy that allows a humanoid robot to autonomously build a representation of its workspace: we call this representation Reachable Space Map. Interestingly, the robot can use this map to: (i) estimate the Reachability of a visually detected object (i.e. judge whether the object can be reached for, and how well, according to some performance metric) and (ii) modify its body posture or its position with respect to the object to achieve better reaching. The robot learns this map incrementally during the execution of goal-directed reaching movements; reaching control employs kinematic models that are updated online as well. Our solution is innovative with respect to previous works in three aspects: the robot workspace is described using a gaze-centered motor representation, the map is built incrementally during the execution of goal-directed actions, learning is autonomous and online. We implement our strategy on the 48-DOFs humanoid robot Kobian and we show how the Reachable Space Map can support intelligent reaching behavior with the whole-body (i.e. head, eyes, arm, waist, legs). (C) 2014 Elsevier B.V. All rights reserved.

While robots are often used in autism therapy, the Uncanny valley effect was never studied in subjects with Autistic Spectrum Disorder (ASD). Since persons with ASD have trouble understanding body language, they react differently to the Uncanny valley. In this paper, we propose to investigate the possible difference in the Uncanny valley's perception of an emotional humanoid robot in subjects with ASD and subjects without ASD. Thirty four adult participants (N = 34, control: 19, ASD: 15; age: 28.5) were asked to watch videos of an emotional humanoid robot and rate its emotions and its gait (Perceived Humanness, Eeriness and Attractiveness). We have found differences between the two groups in their perception of the robot's Perceived Humanness (p &lt; .05). Also, while the ASD group performed as well as the control group for emotion recognition task, we found that the ASD group is more sensible to the Uncanny valley effects than the control group. Finally we conclude on what our findings bring to the Human Robot Interaction field.

The falling of a biped humanoid robot is treated as an extremely unstable state. When an unexpected fall happens, it may cause serious damage to both the robot itself. This study focuses on the falling issue and investigates the effect of the "torso protective strategy" for safe landing of a biped humanoid robot. First, the effectiveness of the torso strategies to the safe landing is analyzed from an energy variation perspective of the robot system. The torso strategies are used to do negative work that reduced the energy of the robot system, thereby reducing the impact velocity of the robot. Then, a comparative simulation is made on a model of humanoid robot to validate the influence of the torso strategies on safe landing.

In this paper, we describe the development of a leg with a rotational joint that mimics the elastic characteristics of the leg of a running human. The purpose of this development was to realize the dynamics of human running, the analysis of which has revealed that the motion of the leg can be modeled by a compression spring and that of the leg joint by a torsion spring. We, therefore, assumed that these elastic characteristics could be used to develop robots capable of human-like running, which requires higher output power than that of existing humanoid robots. Hence, we developed a model of a leg with a rotational joint and fabricated the leg by incorporating a mechanism comprising of two leaf springs for adjusting the joint stiffness. By this means, we were able to achieve human-like joint stiffness, which could be adjusted by varying the effective length of one of the leaf springs. We evaluated the performance of the adjustable stiffness of the joints, and were also able to achieve hopping by resonance of the rotational leg joint.

We propose a new biped locomotion planning method that optimizes locomotion speed subject to friction constraints. For this purpose we use approximate models of required coefficient of friction (RCOF) as a function of gait. The methodology is inspired by findings in human gait analysis, where subjects have been shown to adapt spatial and temporal variables of gait in order to reduce RCOF in slippery environments. Here we solve the friction problem similarly, by planning on gait parameter space: namely foot step placement, step swing time, double support time and height of the center of mass (COM). We first used simulations of a 48 degrees-of-freedom robot to estimate a model of how RCOF varies with these gait parameters. Then we developed a locomotion planning algorithm that minimizes the time the robot takes to reach a goal while keeping acceptable RCOF levels.
Our physics simulation results show that RCOF-aware planning can drastically reduce slippage amount while still maximizing efficiency in terms of locomotion speed. Also, according to our experiments human-like stretched-knees walking can reduce slippage amount more than bent-knees (i.e. crouch) walking for the same speed.

Although consistent stability is desirable, a biped humanoid robot encounters a high risk of falling. Such falls may cause serious damage to both the robot and the environment. This study focuses on this issue and investigates four strategies based on human protective falling motion. These strategies are: "knee flexion", "torso flexion forward", "torso translation backward" and "knee stretched". First, the effectiveness of the strategies for the safe landing is analyzed from an energy variation perspective of the robot system. The four strategies are used to do negative work that reduced the energy of the robot system, thereby reducing the impact velocity of the robot. Then, a simulation study on a human-sized humanoid robot is conducted to assess the influence of the strategies on safe landing. Finally, based on the simulation results for each strategy, a safe falling motion control method is proposed and validated through simulation.

We present a grid-based 3D reconstruction method which integrates all costs given by stereo vision into what we call a Cost-Curve Occupancy Grid (CCOG). Occupancy probabilities of grid cells are estimated in a Bayesian formulation, from the likelihood of stereo cost measurements taken at all distance hypotheses. This is accomplished with only a small set of probabilistic assumptions which we discuss in the paper. We quantitatively characterize the method's performance under different conditions of both image noise and number of used stereo pairs, compared also to traditional algorithms. We complement the study by giving insights on design choices of CCOGs such as likelihood model, window size of the cost function and use of a hole filling method. Experiments were made on a real-world outdoors dataset with ground-truth data.

This paper describes the development of a robotic head that has cartoon facial expression ability with comic marks. For communicating with humans, robots should have expressive facial expression ability for indicating their inner state. Our previous research suggests that robots can express its emotion clearly if it performs facial expressions that are adapted to the cultural background of the communication partner. As a first step, we focus on making expressions for Japanese people. Comic mark is a unique and famous way of emotion expression in Japanese culture. First, we defined facial expressions by combining cartoon-like shape of the facial parts with high emotion recognition rates. Then we asked cartoonists to draw comic marks which they think are effective for emotion expression and find the effective comic marks as "Cross popping veins" for "Anger", "Tear mark" for "Sadness" and "Vertical lines" for "Fear". Finally we obtained a model expression which has sufficiently high emotion recognition rate from the combination of the facial expression and the comic marks. In order to achieve these expressions, we developed flexible full color LED display matrix module and mechanism that push and pull the sheet for expressing black lines. Results of experimental evaluation shows that the new robotic head has over 90% average emotion recognition rates for each of the six basic emotions. The results with non-Japanese subjects suggests that impression of emotion expression on robotic head changes depending on the cultural background. These findings encourage us in pursuing this concept of designing robots that display emotions that are adapted to cultural background of communication partner.

We propose a new heel-contact toe-off walking model based on the Linear Inverted Pendulum (LIP) model, which due to the linearity and the ease of manipulation of the equations, could be considered to be advantageous for a future online implementation for the generation of walking patterns. This new model is based on the so called functional rockers of the foot (heel, ankle and forefoot rockers), each of which are modeled as an inverted pendulum, changing the ground contact point position of the inverted pendulums for each rocker. We focus on the motion of the Center of Mass (CoM) in the sagittal plane, as it is the plane on which the rockers take place, but also generate the motions on the frontal plane. The model proved to work for constant velocity, accelerating and decelerating gaits, and the effects of the change of pivot point during heel-contact toe-off could be corroborated in the Zero Moment Point (ZMP) graphs. The implementation of this model could improve the human likeness of the motions, as well as the stability of the locomotion.

Humanoid robots have this formidable advantage to possess a body quite similar in shape to humans. This body grants them, obviously, locomotion but also a medium to express emotions without even needing a face. In this paper we propose to study the effects of emotional gaits from our biped humanoid robot on the subjects' perception of the robot (recognition rate of the emotions, reaction time, anthropomorphism, safety, likeness, etc.). We made the robot walk towards the subjects with different emotional gait patterns. We assessed positive (Happy) and negative (Sad) emotional gait patterns on 26 subjects divided in two groups (whether they were familiar with robots or not). We found that even though the recognition of the different types of patterns does not differ between groups, the reaction time does. We found that emotional gait patterns affect the perception of the robot. The implications of the current results for Human Robot Interaction (HRI) are discussed.

In this study we describe a terrain-adaptive biped walking control using a new biped foot mechanism with the capability of detecting ground surface. The foot system consists of three spikes each of which has an optical sensor to detect ground height. A robot modifies a foot-landing motion along the vertical axis and about pitch and roll axes according to sensor values, and this enables the robot to walk on unknown uneven terrain. Verification of the proposed control was conducted through experiments with a human-sized humanoid robot WABIAN-2R.

This paper proposes a stiffness analysis of biped walking vehicle that is based on a parallel kinematics architecture. Namely, WL-16RV (Waseda Leg No.16 Refined V) is a biped walking vehicle that can carry on board a human while overcoming typical human environment barriers. Experimental tests have been carried out on a built prototype of WL-16RV by using a specific set up for validation purposes.

Analysis of human running has revealed that the motion of the human leg can be modeled by a compression spring because leg’s joints behave like a torsion spring. In addition, the pelvic movement in the frontal plane contributes to the increase in jumping force. We therefore assumed that human-like running, which requires higher output power than that of existing humanoid robots, could be realized based on these characteristics. Hence, we developed a model composed of a body mass, a pelvis and a rotational joint leg, and fabricated the leg by incorporating a stiffness adjustment mechanism that uses two leaf springs. In this way, we were able to achieve a human-like joint stiffness, which could be adjusted by varying the effective length of one of the leaf springs. We achieved hopping by resonance of the pelvic movement and joints’ elasticity.

The design of what a robot could look like is a matter of growing importance. Variations of style, size, shape and colour open endless design possibilities. It is important to create a look that poses no visual uncanny valley effects on the human user and that is appropriate to potentially serve in different job areas in human society. In this paper we want to share the methods applied in the design of a new head for the humanoid robot KOBIAN-R. Our creation process is similar to that of the product design process taking into account the psychology of shape, colour and functionality to name a few. Following the creative process we conducted some surveys to assess our new design. Feedback data from participants from a diverse age range and cultural backgrounds are a precious input towards the future development of this robotic head.

This paper describes the development of a robotic head with ability to display marks commonly used in ‘‘manga’’ (Japanese comics). To communicate with humans, robots should have an expressive facial expression ability for indicating its inner state. Our previous research suggests that, robots can express its emotion clearly if it perform facial expressions that can adapt with the cultural background of the communication partner. As a first step, we focus on making expressions for Japanese people. Manga mark is a unique and famous way of emotion expression in Japanese culture. In a previous preliminary experiment, we determined facial expressions for the robot KOBIAN-R with manga marks. Those expressions included four manga marks as ‘‘Cross popping veins’’ for ‘‘Anger’’, ‘‘Tear mark’’ for ‘‘Sadness’’, ‘‘Vertical lines’’ for ‘‘Fear’’ and ‘‘Wrinkle’’ for ‘‘Disgust’’. A new head that express these marks was developed. Flexible full color LED matrix display and mechanism for indicating black lines were implemented. Experimental evaluation shows that the new robotic head has over 90% average emotion recognition rates by 30 Japanese participants for each of the six emotions.

Human running motion can be modeled by a spring loaded inverted pendulum (SLIP). However, this model, despite being widely used in robotics, does not include human-like pelvic motion. In this study, we show that the pelvis actually contributes to the increase in jumping force and absorption of landing impact, both of which findings can be used to improve running robots. On the basis of the analysis of human running motion, we propose a new model named SLIP 2 (spring loaded inverted pendulum using pelvis). This model is composed of a body mass, a pelvis, and leg springs; the model can control its springs during running by use of pelvic movement in the frontal plane. To achieve hopping and running motions, we developed pelvis oscillation control, running velocity control, and stabilization control using an upper body, as control methods. We also developed a new hopping robot using the SLIP 2 model. To evaluate the proposed model and control methods, we performed hopping and running simulations. The simulation results showed that the SLIP 2 model successfully achieves hopping and running motions. The hopping robot was also able to accomplish hopping motion. The simulation results also showed that the difference between the pelvic rotational phase and the phase of oscillation of the mass vertical displacement affects the jumping force. In particular, the results revealed that the human-like pelvic rotation contributes to the absorption of landing impact and to the increase in takeoff forces, which validates our observations in human motion analysis.

This paper describes the bipedal humanoid robot that makes human laugh with its whole body expression and affect human's psychological state. In order to realize "Social interaction" between human and robot, the robot has to affect human's psychological state actively. We focused on "laugh" because it can be thought as a typical example for researching "Social interaction". Looking through a Japanese comedy style called "manzai" or the art of conversation, we picked out several methods for making human laugh. Then we made several skits with the advice of comedians, and made the whole body humanoid robot perform them. Results of experimental evaluation with these skits shows that the robot's behavior made subjects laugh and change their psychological state seen as a decrease of "Depression" and "Anger".

This paper describes a walking stabilization control for a biped humanoid robot with narrow feet. Most humanoid robots have larger feet than human beings to maintain their stability during walking. If robot's feet are as narrow as humans, it is difficult to realize a stable walk by using conventional stabilization controls. The proposed control modifies a foot placement according to the robot's attitude angle. If a robot tends to fall down, a foot angle is modified about the roll axis so that a swing foot contacts the ground horizontally. And a foot-landing point is also changed laterally to inhibit the robot from falling to the outside. To reduce a foot-landing impact, a virtual compliance control is applied to the vertical axis and the roll and pitch axes of the foot. Verification of the proposed method is conducted through experiments with a biped humanoid robot WABIAN-2R. WABIAN-2R realized a knee-bended walking with 30 mm breadth feet. Moreover, WABIAN-2R mounted on a human-like foot mechanism mimicking a human's foot arch structure realized a stable walking with the knee-stretched, heel-contact, and toe-off motion.

As witnessed in several behavioural studies, a complex relationship exists between people's cultural background and their general acceptance towards robots. However, very few studies have investigated whether a robot's original language and gesture based on certain culture have an impact on the people of the different cultures. The purpose of this work is to provide experimental evidence which supports the idea that humans may accept more easily a robot that can adapt to their specific culture. Indeed, improving acceptance and reducing discomfort is fundamental for future deployment of robots as assistive, health-care or companion devices into a society. We conducted a Human-Robot Interaction experiment both in Egypt and in Japan. Human subjects were engaged in a simulated video conference with robots that were greeting and speaking either in Arabic or in Japanese. The subjects completed a questionnaire assessing their preferences and their emotional state, while their spontaneous reactions were recorded in different ways. The results suggest that Egyptians prefer the Arabic robot, while they feel a sense of discomfort when interacting with the Japanese robot; the opposite is also true for the Japanese. These findings confirm the importance of the localisation of a robot in order to improve human acceptance during social human-robot interaction.

Emotion display through facial expressions is an important channel of communication. However, between humans there are differences in the way a meaning to facial cues is assigned, depending on the background culture. This leads to a gap in recognition rates of expressions: this problem is present when displaying a robotic face too, as a robot's facial expression recognition is often hampered by a cultural divide, and poor scores of recognition rate may lead to poor acceptance and interaction. It would be desirable if robots could switch their output facial configuration flexibly, adapting to different cultural backgrounds. To achieve this, we made a generation system that produces facial expressions and applied it to the 24 degrees of freedom head of the humanoid social robot KOBIAN-R, and thanks to the work of illustrators and cartoonists, the system can generate two versions of the same expression, in order to be easily recognisable by both Japanese and Western subjects. As a tool for making recognition easier, the display of Japanese comic symbols on the robotic face has also been introduced and evaluated. In this work, we conducted a cross-cultural study aimed at assessing this gap in recognition and finding solutions for it. The investigation was extended to Egyptian subjects too, as a sample of another different culture. Results confirmed the differences in recognition rates, the effectiveness of customising expressions, and the usefulness of symbols display, thereby suggesting that this approach might be valuable for robots that in the future will interact in a multi-cultural environment.

This study describes a biped walking stabilization based on gait analysis for a humanoid robot. So far, we have developed a humanoid robot as a human motion simulator which can quantitatively evaluate welfare and rehabilitation instruments instead of human subjects. However, the walking motion of the robot looked like human's in our past researches, but a walking stabilization control was not based on gait analysis. To use a humanoid robot as a human motion simulator, not only mechanisms but also a stabilizer should be designed based on human beings. Of course, there are many studies on gait analysis in the field of neuroscience, but most of them are not modeled enough to be implemented on humanoid robots. Therefore, first, we conducted gait analysis in this study, and we obtained following two findings: (i) a foot-landing point exists on the line joining the stance leg and the projected point of center of mass on the ground, and (ii) the distance between steps is modified to keep mechanical energy at the landing within a certain value. A walking stabilization control is designed based on the gait analysis. Verification of the proposed control is conducted through experiments with a human-sized humanoid robot WABIAN-2R.

Communication between humans and robots is a very important aspect in the field of Humanoid Robotics. For a natural interaction, robots capable of nonverbal communication must be developed. However, despite the most recent efforts, robots still can show only limited expression capabilities. The purpose of this work is to create a facial expression generator that can be applied to the 24 DoF head of the humanoid robot KOBIAN-R. In this manuscript, we present a system that based on relevant studies of human communication and facial anatomy can produce thousands of combinations of facial and neck movements. The wide range of expressions covers not only primary emotions, but also complex or blended ones, as well as communication acts that are not strictly categorized as emotions. Results showed that the recognition rate of expressions produced by this system is comparable to the rate of recognition of the most common facial expressions. Context-based recognition, which is especially important in case of more complex communication acts, was also evaluated. Results proved that produced robotic expressions can alter the meaning of a sentence in the same way as human expressions do. We conclude that our system can successfully improve the communication abilities of KOBIAN-R, making it capable of complex interaction in the future.

Walking is one of the most common activities that we perform every day. If the main goal of walking is to go from a point A to a point B, walking can also convey emotional clues in social context. Those clues can be used to improve interactions or any messages we want to express. We observed a professional actress perform emotive walking and analyzed the recorded data. For each emotion, we found characteristic features which can be used to model gait patterns for humanoid robots. The findings were assessed by subjects who were asked to recognize the emotions displayed in the acts of walking. © 2013 IEEE.

We propose a two-stage gait pattern generation scheme for the full-scale humanoid robots, that considers the dynamics of the system throughout the process. The fist stage is responsible for generating semi-dynamically consistent step position and step time information, while the second stage incorporated with multi-body dynamics system is responsible for generation of gait pattern that is feasible and stable on the full-scale multi-degree-of-freedom humanoid robot. The approach allows for very rapid gait pattern regeneration during the swing phase of motion and includes information about present dynamic state when regenerating the new pattern. The paper contains description of a developed method, as well as experimental results proving its effectiveness.

Humanoid robots progress everyday closer and closer to a more stable walking suitable for a human environment as the researchers in the Humanoid robotics field focus their effort on the understanding of the human locomotion. Nonetheless for Social Robotics researchers, humanoid robots might have another use, such as being our companions from birth to nursing home. Designing social humanoid robots is one critical step if we want the robots to be active in our society. However, to our knowledge, only a few studies in the area of humanoid robotics have addressed emotion expression with robot gaits. In this paper we propose to assess different emotional gait patterns and the perception of the emotion intensity in those patterns. Actors' emotional movement were captured and then normalized for our robot platform. Several robot simulations were shown to human observers who completed a survey questionnaire in which they indicated their assessment of the portrayed emotion by the robot simulation. The surveyed emotions consist of Sadness, Happiness, Anger, Fear with different intensities (Intermediate, High and Exaggerated). We achieved a high recognition rate of emotions (72.32%). Even if the intensities were less well recognized (33.63%), our study indicates that the intensity might help the recognition of emotional walking.

In this paper, we describe a human gesture recognition system developed to make a humanoid robot understand non-verbal human social behaviors, and we present the results of preliminary experiments to demonstrate the feasibility of the proposed method. In particular, we have focused on the detection and recognition of laughter, a very peculiar human social signal. In fact, although it is a direct form of social interaction, laughter is classified as semi voluntary action, can be elicited by several different stimuli, and it is strongly associated with positive emotion and physical well-being. The possibility of recognize, and further elicit laughter, will help the humanoid robot to interact in a more natural way with humans, to build positive relationships and thus be more socially integrated in the human society.

Extensive literature has been written on occupancy grid mapping for different sensors. When stereo vision is applied to the occupancy grid framework it is common, however, to use sensor models that were originally conceived for other sensors such as sonar. Although sonar provides a distance to the nearest obstacle for several directions, stereo has confidence measures available for each distance along each direction. The common approach is to take the highest-confidence distance as the correct one, but such an approach disregards mismatch errors inherent to stereo.
In this work, stereo confidence measures of the whole sensed space are explicitly integrated into 3D grids using a new occupancy grid formulation. Confidence measures themselves are used to model uncertainty and their parameters are computed automatically in a maximum likelihood approach. The proposed methodology was evaluated in both simulation and a real-world outdoor dataset which is publicly available. Mapping performance of our approach was compared with a traditional approach and shown to achieve less errors in the reconstruction.

We present a novel control architecture for the integration of visually guided walking and whole-body reaching in a humanoid robot.We propose to use robot gaze as a common reference frame for both locomotion and reaching, as suggested by behavioral neuroscience studies in humans. A gaze controller allows the robot to track and fixate a target object, and motor information related to gaze control is then used to i) estimate the reachability of the target, ii) steer locomotion, iii) control whole-body reaching. The reachability is a measure of how well the object can be reached for, depending on the position and posture of the robot with respect to the target, and it is obtained from the gaze motor information using a mapping that has been learned autonomously by the robot through motor experience: we call this mapping Reachable Space Map. In our approach, both locomotion and whole-body movements are seen as ways to maximize the reachability of a visually detected object, thus i) expanding the robot workspace to the entire visible space and ii) exploiting the robot redundancy to optimize reaching. We implement our method on a full 48-DOF humanoid robot and provide experimental results in the real world.

We propose a two-stage gait pattern generation scheme for the full-scale humanoid robots, that considers the dynamics of the system throughout the process. The fist, stage is responsible for generating the preliminary motion reference, such as step position, timing and trajectory of Center of Mass (CoM), while the second stage serves as dynamics filter which employs a multi-body model and based on Zero Moment Point (ZMP) reference trajectory generates CoM reference trajectory which defines a locomotion stable when executed on the full-scale multi-degree-of-freedom humanoid robot. The approach thanks to introducing a dynamic model at, the stage of feet placement planning provides the ZMP reference, which is ensured to be feasible for the robot. Thanks to the fact it enables instantaneous regeneration of motion. The paper contains description of two approaches used in the first and second stage, as well as experimental results proving the effectiveness of the method. The fast calculation time and the use of the system's dynamic state as initial conditions for pattern generation makes it a good candidate for the real-time gait pattern generator.

Designing humanoid robots able to interact socially with humans is a challenging task. If we want the robots to be actively integrated in our society, several issues have to be taken in account: the look of the robot, the naturalness of its movements, the stability of its walk, the reactivity it might have with its human partners. We propose to improve the reactivity of the robot by using a emotional mental model in order to generate emotional gait patterns. Those patterns will help the understanding of any emotional message conveyed between a human and a robot. We propose a novel emotional gait generation method based on the Emotion mental model. We did preliminary experiments with the Happiness and Sadness emotions and with different intensities.

A complex relationship exists between national cultural background and interaction with robots, and many earlier studies have investigated how people from different cultures perceive the inclusion of robots into society. Conversely, very few studies have investigated how robots, speaking and using gestures that belong to a certain national culture, are perceived by humans of different cultural background. The purpose of this work is to prove that humans may better accept a robot that can adapt to their specific national culture. This experiment of Human-Robot Interaction was performed in Egypt. Participants (native Egyptians versus Japanese living in Egypt) were shown two robots greeting them and speaking respectively in Arabic and Japanese, through a simulated video conference. Spontaneous reactions of the human subjects were measured in different ways, and participants completed a questionnaire assessing their preferences and their emotional state. Results suggested that Egyptians prefer the Arabic version of the robot, while they report discomfort when interacting with the Japanese version. These findings confirm the importance of a culture-specific customisation of robots in the context of Human-Robot Interaction. © 2013 IEEE.

The understanding of emotions in humans is really important in the Human-Robot Interaction field. The affective state of a person can be expressed in several ways, one of them being through the way we walk and our gait can convey emotional clues in social context. Those clues can be used to improve the personal interactions with our peers or add meaning to any message we want to express. However, only a few studies in humanoid robotics were done on the effects of the emotions on the walking. In this paper, we propose to assess the emotional walking patterns created from motion capture data with a survey. Those patterns represent different emotions (sadness, happiness) with different intensities (middle, high and exaggerated). Those emotional walking patterns achieved a high recognition rate of the emotions and the subjects (N=13) could recognize whole body emotions without facial expression on our humanoid robot. Additionally, we found out that at first people might perform poorly at recognizing emotions and their intensities but can get better, even without correction or feedback on their performances. © 2013 IEEE.

There are several problems which arise when using a standard ZMP-based pattern generator to control an intrinsically compliant humanoid robot like COMAN. We present two techniques: pelvis forward trajectory smoothing and polynomial admittance gain modulation, which make it possible to use the conventional pattern generator to control such passively compliant robots. The former method modifies the reference of the pelvis trajectory to counteract its overshooting caused by the compliance of the legs. The latter method is meant to decrease the impact during initial contact and decrease the error between the foot position and original reference during the mid-stance caused by the use of admittance control. We explain details of both of the methods and show results from walking experiments with and without the controls, proving their effectiveness.

Walking is one of the most common activities that we perform every day. Even if the main goal of walking is to move from one place to another place, walking can also convey emotional clues in social context. Those clues can be used to improve interactions or any messages we want to express. However, there are not many studies on the effects of the intensity of the emotions on the walking. In this paper, the authors propose to assess the differences between the expression of emotion regarding the expressed intensity (low, middle, high and exaggerated). We observed two professional actors perform emotive walking, with different intensities and we analyzed the recorded data. For each emotion, we analyzed characteristic features which can be used in the future to model gait patterns and to recognize emotions from the gait parameters. Additionally, we found characteristics which can be used to create new emotion expression for our biped robot Kobian, improving the human-robot interaction.

In this study we describe a shoes-wearable foot mechanism which mimics human's foot arch structure and the characteristics of the foot skin to examine the effect of the human foot on biped walking. We approximate the arch structure by a rotational spring and model the human's foot skin with compression springs. The mimesis of the foot arch elasticity is realized by using compression springs. Regarding the characteristics of human's foot skin, first we develop a measuring equipment to measure the human's plantar transverse elasticity. We set the target value of the modulus of transverse elasticity of the foot skin to 11.2 N/mm, and we set the modulus of compression elasticity to 0.136 MPa, referring to a relevant study. The characteristics of human's foot skin are mimicked by using a super-soft urethane resin called Hitohada-gel with 8 mm thick. Through evaluation tests we confirmed that the shoes-wearable foot mechanism could mimic well the characteristics of human's foot arch and skin. © 2013 IEEE.

This paper describes the development of a new shank mechanism and mimicking the human-like walking in the horizontal and frontal plane. One of human walking characteristics is that the COM (Center Of Mass) motion in the lateral direction is as small as 30 mm. We assume that it is thanks to the human walking characteristics in the horizontal plane that the step width is as narrow as 90 mm and the foot rotation angle is 12 deg. To mimic these characteristics, we developed a new shank and implemented it in a humanoid robot WABIAN-2RIII. It has a parallel mechanism which mimics the shank's size of human. Thanks to its size almost the same as human's the robot is capable of realizing gait with the narrow step width of 90 mm and the foot rotation angle of 12 deg. We evaluated the performance of the shank using WABIAN-2RIII. The robot could realize stepping in place with lateral displacement of CoM within 34 mm, which is almost as small as that of human. © 2013 IEEE.

This paper describes the implementation in a walking humanoid robot of a mental model, allowing the dynamical change of the emotional state of the robot based on external stimuli; the emotional state affects the robot decisions and behavior, and it is expressed with both facial and whole-body patterns. The mental model is applied to KOBIAN-R, a 65-DoFs whole body humanoid robot designed for human-robot interaction and emotion expression. To evaluate the importance of the proposed system in the framework of human-robot interaction and communication, we conducted a survey by showing videos of the robot behaviors to a group of 30 subjects. The results show that the integration of dynamical emotion expression and locomotion makes the humanoid robot more appealing to humans, as it is perceived as more "favorable" and "useful", and less "robot-like."

Walking is one of the most common activities that we perform every day. If the main goal of walking is to go from a point A to a point B, walking can also convey emotional clues in social context. Those clues can be used to improve interactions or any messages we want to express. We observed a professional actress perform emotive walking and analyzed the recorded data. For each emotion, we found characteristic features which can be used to model gait patterns for humanoid robots. The findings were assessed by subjects who were asked to recognize the emotions displayed in the acts of walking.

The authors propose a comparison between two force-position controllers with gravity compensation simulated on the DEXTER bioinspired robotic arm. The two controllers are both constituted by an internal proportional-derivative (PD) closed-loop for the position control. The force control of the two systems is composed of an external proportional (P) closed-loop for one system (P system) and an external proportional-integrative (PI) closed-loop for the other system (PI system). The simulation tests performed with the two systems on a planar representation of the DEXTER, an eight-DOF bioinspired arm, showed that by varying the stiffness of the environment, with a correct setting of parameters, both systems ensure the achievement of the desired force regime and with great precision the desired position. The two controllers do not have large differences in performance when interacting with a lower stiffness environment. In case of an environment with greater rigidity, the PI system is more stable. The subsequent implementation of these control systems on the DEXTER robotic bioinspired arm gives guidance on the design and control optimisation of the arms of the humanoid robot named SABIAN. © 2013 Giovanni Gerardo Muscolo et al.

In this paper we describe how a humanoid robot can learn a representation of its own reachable space from motor experience: a Reachable Space Map. The map provides information about the reachability of a visually detected object (i.e. a 3D point in space). We propose a bio-inspired solution in which the map is built in a gaze-centered reference frame: the position of a point in space is encoded with the motor configuration of the robot head and eyes which allows the fixation of that point. We provide experimental results in which a simulated humanoid robot learns this map autonomously and we discuss how the map can be used for planning whole-body and bimanual reaching. © 2012 IEEE.

This paper describes a walking stabilization control on a soft ground based on gait analysis for a biped humanoid robot. There are many studies on gait analysis on a hard ground, but few physiologists analyze the walking ability of human beings on a soft ground. Therefore, we conducted anthropometric measurement using VICON motion capture system on a soft ground. By analyzing experimental results, we obtained three findings. The first finding is that step height tends to increase to avoid tripping on a soft ground but there are no significant differences in step length and step width. The second finding is that although the CoM amplitude increases in the vertical direction on a soft ground, there are no significant differences in the CoM trajectories in the lateral direction. The last finding is that the head is stabilized during walking not only on a hard ground but also on a soft ground. Based on these findings, we developed a novel walking stabilization control to stabilize the CoM motion in the lateral direction on a soft ground. Verification of the proposed control is conducted through experiments with a human-sized humanoid robot WABIAN-2R. The experimental videos are supplemented. © 2012 IEEE.

Human-Robot Interaction is one of the biggest challenges in Humanoid Robotics. Interaction can be carried out through different channels, as humans can communicate through complex languages, including the use of non-verbal communication. Specifically, facial expressions are important for conveying emotions and communication intentions. Several humanoid robots can already perform a certain set of expressions, but their capabilities are somewhat limited and as a result, interaction is not natural. One aspect that could help robots being perceived as real is asymmetry. That is why in this paper we perform an evaluation study of symmetrical and asymmetrical facial expressions of the humanoid robot KOBIAN-R. These expressions are made by a generator based on relevant studies of facial anatomy and non-verbal communication and on the work of illustrators and cartoonists. Survey results confirmed the effectiveness of the generator and the importance of asymmetry. We conclude that using this system, robot communication capabilities improve, making possible the development of more advanced interaction in the future.

This paper describes a walking stabilization control on a soft ground based on gait analysis for a humanoid robot. There are many researches on gait analysis on a hard ground, but few scientists analyze the walking ability of human beings on a soft ground. Therefore, we conducted anthropometric measurement using a motion capture system on a soft ground. By analyzing experimental data, we obtained two findings. The first finding is that although there are no significant differences in step width and step length, step height tends to increase to avoid the collision between the feet and a soft ground. The second finding is that there are no significant differences in the lateral CoM trajectories but the vertical CoM amplitude increases when walking on a soft ground. Based on these findings, we developed a walking stabilization control to stabilize the CoM motion in the lateral direction on a soft ground. Verification of the proposed control is conducted through experiments with a human-sized humanoid robot WABIAN-2R. The experimental videos are supplemented.

This paper describes the development of a new expressive robotic head for the bipedal humanoid robot. Facial expressions of our old robotic head have low facial expression recognition rate and in order to improve it we asked amateur cartoonists to create computer graphics (CG) images. To realize such expressions found in the CGs, the new head was provided with 24-DoFs and facial color. We designed compact mechanisms that fit into the head, which dimensions are based on average adult Japanese female size. We conducted a survey with pictures and videos to evaluate the expression ability. Results showed that facial expression recognition rates for the 6 basic emotions are increased compared to the old KOBIAN's head.

The results of the neuroscientific research show that humans tend to stabilize the head orientation during locomotion. In this paper we describe the implementation of inverse kinematics based head stabilization controller on the humanoid platform. The controller uses the IMU feedback and controls neck joints in order to align the head orientation with the global orientation reference. Thanks to the method, we can decouple the orientational motion of the head from the rest of the body. This way stabilized head becomes better platform for proprioceptive sensory apparatus, such as cameras or IMU. In the paper we present three experiments which prove that the method has good performance in damping both, high and low frequency motion of the head. We also prove that the proposed controller improves the stability of the tracked goal point on the image of in-built camera.

Communication between humans and robots is a very critical step for the integration of social robots into society. Emotion expression through a robotic face is one of the key points of communication. Despite the most recent efforts, no matter how much expression capabilities improve, facial expression recognition is often hampered by a cultural divide between subjects that participate in surveys. The purpose of this work is to take advantage of the 24 degrees of freedom head of the humanoid social robot KOBIAN-R for making it capable of displaying different versions of the same expressions, using face and neck, in a way that they are easy to understand for Japanese and for Western subjects. We present a system based on relevant studies of human communication and facial anatomy, as well as on the work of illustrators and cartoonists. The expression generator we developed can be adapted to specific cultures. Results confirmed the in-group advantage, showing that the recognition rate of this system is higher when the nationality of the subjects and the cultural characterisation of the shown expressions are coincident. We conclude that this system could be used, in future, on robots that have to interact in a social environment, with people with different cultural background. © 2012 Springer-Verlag.

In this work we propose an adaptive model for the head stabilization based on a feedback error learning (FEL). This model is capable to overcome the delays caused by the head motor system and adapts itself to the dynamics of the head motion. It has been designed to track an arbitrary reference orientation for the head in space and reject the disturbance caused by trunk motion. For efficient error learning we use the recursive least square algorithm (RLS), a Newton-like method which guarantees very fast convergence. Moreover, we implement a neural network to compute the rotational part of the head inverse kinematics. Verification of the proposed control is conducted through experiments with Matlab SIMULINK and a humanoid robot SABIAN. © 2012 IEEE.

In this paper we describe how a humanoid robot can learn a representation of its own reachable space from motor experience: a Reachable Space Map. The map provides information about the reachability of a visually detected object (i.e. a 3D point in space). We propose a bio-inspired solution in which the map is built in a gaze-centered reference frame: the position of a point in space is encoded with the motor configuration of the robot head and eyes which allows the fixation of that point. We provide experimental results in which a simulated humanoid robot learns this map autonomously and we discuss how the map can be used for planning whole-body and bimanual reaching.

The neuroscientific research shows that humans tend to stabilize their head orientation, while accomplishing a locomotor task. In order to replicate head movement behaviors found in human walk it is necessary and sufficient to be able to control the orientation (roll, pitch and yaw) of the head in space. The described behaviors can be replicated by giving suitable references to the head orientation. Based on these principles, a model based on an inverse kinematics controller has been designed. In this paper we introduce implementation of the model on a humanoid platform. Along we present results of two sets of experiments performed to verify two aspects of the proposed model. The results prove that the model can be used to efficiently stabilize the head's orientation.

This paper describes a walking stabilization control on a soft ground based on gait analysis for a biped humanoid robot. There are many studies on gait analysis on a hard ground, but few physiologists analyze the walking ability of human beings on a soft ground. Therefore, we conducted anthropometric measurement using VICON motion capture system on a soft ground. By analyzing experimental results, we obtained three findings. The first finding is that step height tends to increase to avoid tripping on a soft ground but there are no significant differences in step length and step width. The second finding is that although the CoM amplitude increases in the vertical direction on a soft ground, there are no significant differences in the CoM trajectories in the lateral direction. The last finding is that the head is stabilized during walking not only on a hard ground but also on a soft ground. Based on these findings, we developed a novel walking stabilization control to stabilize the CoM motion in the lateral direction on a soft ground. Verification of the proposed control is conducted through experiments with a human-sized humanoid robot WABIAN-2R. The experimental videos are supplemented.

This paper describes a walking stabilization control based on gait analysis for a biped humanoid robot. We have developed a human-like foot mechanism mimicking the medial longitudinal arch to clarify the function of the foot arch structure. To evaluate the arch function through walking experiments using a robot, a walking stabilization control should also be designed based on gait analysis. Physiologists suggest the ankle, hip and stepping strategies, but these strategies are proposed by measuring human beings who are not "walking" but "standing" against force disturbances. Therefore, first we conducted gait analysis in this study, and we modeled human walking strategy enough to be implemented on humanoid robots. We obtained following two findings from gait analysis: i) a foot-landing point exists on the line joining the stance leg and the projected point of CoM on the ground, and ii) the distance between steps is modified to keep mechanical energy at the landing within a certain value. A walking stabilization control is designed based on the gait analysis. Verification of the proposed control is conducted through experiments with a human-sized humanoid robot WABIAN-2R. The experimental videos are supplemented.

We present an autonomous goal-directed strategy to learn how to control a redundant robot in the task space. We discuss the advantages of exploring the state space through goal-directed actions defined in the task space (i.e. learning by trying to do) instead of performing motor babbling in the joints space, and we stress the importance of learning to be performed online, without any separation between training and execution. Our solution relies on learning the forward model and then inverting it for the control
different approaches to learn the forward model are described and compared. Experimental results on a simulated humanoid robot are provided to support our claims. The robot learns autonomously how to perform reaching actions directed toward 3D targets in task space by using arm and waist motion, not relying on any prior knowledge or initial motor babbling. To test the ability of the system to adapt to sudden changes both in the robot structure and in the perceived environment we artificially introduce two different kinds of kinematic perturbations: a modification of the length of one link and a rotation of the task space reference frame. Results demonstrate that the online update of the model allows the robot to cope with such situations. © 2011 IEEE.

Humanoid robots are becoming an important factor for the future work. Future planes are made for the use of humanoid robots for space and planetary exploration application. The development of humanoid robot to work in such environment for the purpose of human assisting is becoming highly demanded. The challenge of developing a bipedal robot to walking on other planets and moons is really high due the different in gravity compare to earth. The difference in the gravity might have a great effect on the robot locomotion. In order to know this effect some basic study needed to be conducted. This research studies the effect of different gravity on the locomotion. The approach for dealing for the different gravity is purposed in this study. © 2011 IEEE.

In this paper we present a general strategy for the calculation of the effective Center of Mass (CoM) of humanoid robots, allowing the reduction of the error between the virtual robot model and the real platform. The method is based on an algorithm that calculates the real position of the CoM of a biped humanoid robot using only 2 force/torque sensors located on the feet of the robot. By means of this algorithm, it is possible to reduce the gap between the real and the virtual posture of the robot and consequently the errors between the ZMP trajectory calculated by the offline pattern generator and the ZMP trajectory calculated by the real-time pattern generator of the humanoid robot. Thus, the influence of the real-time control in the static and dynamic balance of a humanoid platform is minimized. Experimental results using SABIAN platform are provided to validate the proposed method. The results support the applicability of the method to more complex systems. © 2011 IEEE.

A four degrees of freedom (DoF) waist and trunk mechanism, as well as human-like foot, enable the humanoid robot WABIAN-2R to perform human-like walk with stretched knees, and heel-contact and toe-off gait phases. The inverse kinematics (IK) method, used in the present system, requires specification of not only task space reference trajectories, but also reference trajectories for all redundant DoFs. In this paper, we propose a novel, unified inverse kinematics method significantly simplifying the pattern generation. The method enables generation of the above described gait by specifying only the task space trajectories. We divide the forward locomotion task into subtasks with different priorities and combine them in the single IK equation. We also perform experiments in simulation environment as well as on WABIAN-2R, which prove that the method can be used to calculate IK for human-like gait. The equation evaluated in this paper is applied to the forward locomotion task, however it can be easily modified to perform other tasks on humanoid robots with different kinematic structures.

This paper describes a fast turning method for a humanoid robot by using slipping motion with both feet. The humanoid robot, WABIAN-2R, has achieved human-like walking with heel contact and toe off motions by using a human-like foot mechanism with a passive toe joint. The human-like foot enables a robot to turn by using slipping motion between the feet and the ground because it can switch ground contact conditions such as heel contact, sole contact and toe contact. To realize a slipping turn, we develop an attitude control. Verification of the proposed method is conducted through experiments with a biped humanoid robot WABIAN-2R. WABIAN-2R realized a quick turn by using slipping motion with both feet. We also confirmed that the energy consumption of a slipping turn is less than that of a stepping turn.

This paper describes an avoidance behavior against unknown forces acting from outside the system on a biped vehicle. External forces that act on a biped vehicle can be divided into two categories: disturbances from the rider of the vehicle and disturbances from outside the system. Disturbances from the rider are measured by a force sensor placed between the rider's seat and the pelvis, while disturbances from outside the system are estimated from zero moment point (ZMP) errors. To guarantee walking stability, the waist position is adjusted to match the measured ZMP to the reference ZMP and the position of the landing foot is adjusted such that the waist trajectory does not diverge. On implementing the developed method on the human-carrying biped robot in an experimental setup, the robot could realize a stable walk even while subjected to unknown external forces in the environment. On applying a pushing force to the walking robot, the robot moved in the pushed direction and away from the source of the externally generated forces. On pushing the robot that was walking forward, the robot stopped moving forward and avoided getting closer to the source of the externally generated forces. We confirmed the effectiveness of the proposed control through these experiments. (C) Koninklijke Brill NV, Leiden and The Robotics Society of Japan, 2011

Personal robots anticipated to become popular in the future are required to be active in joint work and community life with humans. These personal robots must recognize changing environment and must conduct adequate actions like human. Visual tracking can be said as a fundamental function from the view point of environmental sensing and reflex reaction against it. The authors developed a visual tracking motion algorithm by using upper body. Then, we integrated it with an online walking pattern generator and developed a visual tracking biped locomotion. Finally, we conducted an experimental evaluation with emotion expression.

Personal robots anticipated to become popular in the future are required to be active in joint work and community life with humans. These personal robots must recognize changing environment and must conduct adequate actions like human. Visual tracking can be said as a fundamental function from the view point of environmental sensing and reflex reaction against it. The authors developed a visual tracking motion algorithm by using upper body. Then, we integrated it with an online walking pattern generator and developed a visual tracking biped locomotion. Finally, we conducted an experimental evaluation with emotion expression. © 2010 IEEE.

The humanoid robot, WABIAN-2R, has achieved human-like walking with knee-stretched, heel contact and toe off motions by using a foot mechanism with a passive toe joint. However, the foot structure is different from a human's. In this paper, we describe a new foot mechanism capable of mimicking the human's foot arch structure to figure out the function of the arch structure. Especially, the developed foot mimics the elastic properties of the arch of the human's foot and the change of the arch height during walking. The foot mechanism consists of a passive joint in the internal toe, a passive joint in the external toe, and a joint in the foot arch. We conducted several walking experiments by using WABIAN-2R, and the function of the arch structure is clarified quantitatively. As a result, we confirmed that the arch elasticity could absorb a foot-landing force at the plantar contact phase and the change of the arch height contributed to a strong thrust at the push-off phase.

The main goal of this paper is to report a successful attempt of monitoring the stiffness behavior of a biped walking vehicle during its dynamic operation. In particular, a suitable procedure has been developed and implemented for estimating the stiffness performance of WL-16RV as based on previous experiences at LARM with Milli-CaTraSys design. The proposed experimental set-up is composed of six linear encoder wire sensors and two force/torque sensors embedded in each foot. Experimental tests are conducted on a biped walking vehicle WL-16RV under static and dynamic conditions. The experimental tests provide useful information for both design and control purposes.

The humanoid robot, WABIAN-2R, has achieved human-like walking with heel contact and toe off motions with a foot mechanism with a passive toe joint. However, the foot structure is different from a human's. In this paper, we describe a new foot mechanism mimicking the human's foot arch structure to figure out its function. Especially, the developed foot mimics the elastic properties of the arch and the change of the arch height during walking. We conducted several walking experiments by using WABIAN-2R, and we confirmed that the arch elasticity could absorb a foot-landing impact force at the plantar contact phase and the change of the arch height contributed to a strong thrust at the push-off phase.

We have developed a new biped foot mechanism capable of detecting ground surface to realize stable walking on uneven terrain. The size of the foot mechanism is 160 mm x 277 mm and its weight is 1.5 kg. The foot system consists of four spikes each of which has an optical sensor to detect ground height. The foot makes a support polygon on uneven terrain by using three or four spikes. We have conducted several experiments on the outdoor ground surface that has a slope of 7.0 degrees and a maximum height of 15 mm bumps, and the effectiveness of the foot mechanism is confirmed.

This paper describes an avoidance behavior from unknown external forces for a biped walking vehicle. To distinguish between external forces from passenger and those from environments, we use the data of a force sensor mounted on foot, and external forces are estimated from ZMP errors. To guarantee a walking stability, the waist position is adjusted to match the measured ZMP to the reference ZMP, and the position of landing foot is adjusted so that the waist trajectory does not diverge. By implementing the developed method on the human-carrying biped robot, the robot realized a stable walk under unknown external forces from environments. When pushing the robot stepping, the robot moved backward and moved away from the generation source of external forces about 400 mm. When pushing the robot walking forward, the robot stopped going forward and prevented from coming closer to the generation source of external forces. We confirmed the effectiveness of the proposed control through these experiments.

This paper describes about an online pattern generation based on FFT (Fast Fourier Transform). Until now, authors have adopted the offline FFT-based pattern generation. However, it's needed to regard the compensated moment from starting walking to stopping as a periodic function and it's difficult to generate a part of walking pattern. As a solution, it's found that the compensatory waist trajectory for the compensated moment which is cut out with a window of predetermined duration is proper only in the center part of the window. That means the whole trajectory is obtained as a series of the partial ones. Therefore, the online pattern generation is realized by generating a partial trajectories in the proposed way while walking.

This paper describes a disturbance avoidance control from environments for a biped walking vehicle. To distinguish between external forces from passenger and those from environments, we use the data of a force sensor mounted on foot to generate an avoidance behavior. To guarantee a walking stability against external forces. a compensation motion around a reference ZMP is generated. Then, external forces are estimated from ZMP errors. By implementing the developed method on the human-carrying biped robot, the robot realized a stable walk under unknown external forces from environments.

We have developed a biped humanoid robot, WABIAN-2R as a human motion simulator. However, it was difficult to walk stably on terrain with unevenness of several millimeters. So, we propose an attitude compensation control and a landing pattern modification control (LPMC) to deal with uneven terrain. The LPMC modifies the motion of the landing foot according to the ground surface while the attitude control compensates posture angles of the body based on the 3-axis gyro sensor's data. By integrating two controls, WABIAN-2R is able to walk on outdoor terrain with 5 degree inclination slope and height variations of several millimeters.

To increase the maximum payload, the joint arrangement of the Stewart platform type leg mechanism for a biped walking vehicle is optimized by a dynamic simulation and a real-coded genetic algorithm. Using effective joint arrangement, the maximum HMS (root-mean-square) value of the current will be able to be reduced. A new prototype of a biped walking vehicle, WL-16RIV, was developed by using the optimal joint arrangement method. Weight saving in some parts was also conducted. Through walking experiments, the maximum R,MS value of the current, was reduced, and the maximum payload was increased. The effectiveness of the proposed method was confirmed

This paper describes a static disturbance compensation control for a biped walking vehicle. To measure forces and movements caused by a passenger's motion, we use a 6-axis force/torque sensor placed under the passenger's seat. When a small external force acts on a robot, only a reference ZMP trajectory is changed inside a support polygon. When a large external force over a predetermined threshold force acts on a robot, a waist motion is changed. With only the proposed control, however, a robot cannot adapt to rapid changes of external forces. But we have already developed a dynamic disturbance compensation control, so by combining two controls, a human-carrying biped robot, Waseda Leg-No. 16 Refined V (WL-16RV) realized a stable walk under unknown external forces caused by passenger's static and dynamic motion. We confirmed the effectiveness of our proposal through experiments.

Many researchers have studied on walking stability controls for biped robots. Most of them are highly accurate acceleration controls based on the mechanics model of the robot. However, the control algorithms are difficult to be applied to human-carrying biped robots due to modeling errors. In the previous report, we proposed the landing pattern modification method, but it had a problem that a foot landing impact increased when a walking speed became fast. So, we propose a new terrain-adaptive control that can reduce a landing.. impact force. To increase a concave terrain adaptation, e set a target landing position beneath a reference level. To reduce the landing-impact force, we change the position gain control value to a small value at a swing phase. Moreover, we set landing-foot speed at zero after detecting a foot-landing by the force sensor mounted on a foot. To follow uneven terrain, a virtual spring is installed to the vertical direction after detecting a foot-landing on a ground, and a virtual compliance control is applied to the roll and pitch axes. In a stable walk while carrying a 65 kg human on uneven terrain, the new control method decreased the landing-impact force than the previous terrain-adaptive control.

Many researchers have studied on walking stability controls for biped robots. Most of them are highly accurate acceleration controls based on the mechanics model of the robot. However, the control algorithms are difficult to be used for human-carrying biped robots due to modeling errors. In the previous report, we proposed the landing pattern modification method, but it had a problem that a foot landing impact increased when a walking cycle was short. So, we propose a new terrain-adaptive control reducing a landing-impact force. To increase a concave terrain adaptation, we set a target landing position beneath a reference level. To reduce the landing-impact force, we change the position gain control value to a small value at a swing phase. Moreover, we set landing-foot speed at zero when the foot landing is detected by the force sensor mounted on a foot. To follow uneven terrain, a virtual spring is applied along the vertical direction after detecting a foot-landing on a ground, and a virtual compliance control is applied to the roll and pitch axes. In a stable walk while carrying a 65 kg human on uneven terrain, the new control method decreased the landing-impact force than the previous terrain-adaptive control.

This paper describes a static disturbance compensation control for a biped walking vehicle. To measure forces and moments caused by a passenger's motion, we use a 6-axis force/torque sensor placed under the passenger's seat. When small external force acts on a robot, only a reference ZMP trajectory is changed inside a support polygon. When large external force over a predetermined threshold force acts on a robot, a waist motion is changed. With only the proposed control, however, a robot cannot adapt to rapid disturbance changes. But we have already developed a dynamic disturbance compensation control, so by combining two controls, a human-carrying biped robot, Waseda Leg - No. 16 Refined V (WL-16RV) realized a stable dynamic walk under unknown external disturbances caused by passenger's static and dynamic motion. We confirmed the effectiveness of our proposal through experiments.

Many researchers have been studying on walking control methods for biped robots. However, the effectiveness of these control methods was not verified in outdoor environments such as pedestrian roads and gravel roads. In this paper, a landing pattern modification method adaptable to uneven terrain in a real environment is proposed which is based on a predictive attitude compensation control and a nonlinear compliance control. This method does not require any other sensors except force sensors. Also, a new biped foot system is described, which can form larger support polygons on uneven terrain than conventional biped foot systems. Using the pattern modification method and the foot system, WL-16R11 (Waseda Leg - No. 16 Refined II) achieved a stable walk on bumpy terrain with 20 mm height and 10 degrees inclination. Furthermore, a stable dynamic walk was realized in outdoor environment, when a human rode it. Through various walking experiments, the effectiveness of the method is confirmed.

This paper describes a passive dynamic model of a passenger for a biped walking vehicle. The model consists of a lower-limb's model fixed on the robot's waist and a particle model of an upper body connected to the robot's waist through springs and dampers. The stiffness and damping coefficients are verified through waist-shaking experiments by using a force/torque sensor under the seat that is mounted on the robot's waist. A walking pattern generation that enables stable walking even if a passenger sits naturally on the seat is also described. This stable walking pattern is generated by an iteration method based on Fourier Transformation. The effectiveness of the proposed method is confirmed through walking experiments.

Biped walking is easily adaptable to rough terrain such as stairs and stony paths, but the walk speed and energy efficiency on the flat ground is not so effective compared with wheeled locomotion. So, we propose a new control method for a swizzle motion of biped walking robots mounted on inline skates. The swizzle motion uses the friction force generated by periodical movement of passive wheels. The proposed method is based on the reaction force which acts on the foot, and a new reference position is changed according to the reaction force not to be large internal force. Through hardware experiments, the effectiveness of the proposed method was confirmed.

Biped walking is easily adaptable to rough terrain such as stairs and stony paths, but the walk speed and energy efficiency on the flat ground is not so effective compared with wheeled locomotion. This paper describes a motion pattern generation for roller skating of biped walking robots. If the robot's weight is on the standing foot during kicking motion, there will be no sufficient friction for the kicking foot. So, we propose a kicking pattern generation based on ZMP from a kicking phase to a standing phase. Through hardware experiments, a skating motion was realized, and the effectiveness of the proposed method was confirmed.

This paper describes how to compensate unknown external forces caused by a rider's motion of a biped walking vehicle. When external forces act on a robot's waist, the waist is accelerated so that a measured ZMP may be equal to a reference ZMP. To inhibit the divergence of the waist motion, the reference ZMP is varied inside a support polygon. However, if a large external force acts on a robot, the waist trajectory does not converge by only controlling a reference ZMP. So, ZMP trajectory is varied by changing a foot-landing point. Using the proposed control method, WL-16RIV (Waseda Leg - No.16 Refined IV) achieved a stable human-carrying walking under unknown external forces which exert forward and sideways on the robot's waist. Through various walking experiments, the effectiveness of the proposed method was confirmed.

Previously, the realization of ascending and descending stairs and landing pattern modification control by WL-16RII were reported. However, it is difficult to use the landing pattern modification control when ascending stairs, because of the insufficient stroke of linear actuators. In this report, the design of a double stage linear actuator with a larger expansion and contraction ratio is described. The new linear actuators developed have been installed in WL-16RII, and several experiments were conducted. Through experiments involving walking with a wide step length and ascending a stair with landing pattern modification control, the effectiveness of the actuator developed is confirmed.

Many control methods have been studied on the assumption that the feet of biped robots contact the ground with four points. However, it is difficult for almost all of such biped robots to maintain four-point contact on uneven terrains because they have rigid and flat soles. In order to solve the problem, foot mechanisms should be studied. In 2003, we developed WS-1R (Waseda Shoes - No.1 Refined) which is able to maintain four-point contact. However, it is difficult to deal with the concave or convex ground because of the problems of the contact detection and sideways slip. So, WS-5 (Waseda Shoes - No.5) has been developed. To avoid the slip of the foot, a cam-slider locking system consisting of a solenoid and a cam is constructed and installed at the foot. Also, linear encoders are employed to measure the position of the foot sliders. Through walking experiments on uneven terrains, the effectiveness of WS-5 is confirmed.

This paper describes one method to stop suddenly and safely without falling for biped walking robots. It can be implemented with only hardware and without a computer system. This method consists of a braking function attached to leg actuators and a fall avoidance mechanism attached to the robot's foot. Using the human-carrying biped locomotor WL-16RII (Waseda Leg - No.16 Refined II), the effectiveness of the method proposed in this paper was confirmed through an emergency stopping experiment during walking, while carrying a heavy load.

In this paper, the importance of experimental evaluation of stiffness performance is pointed out for evaluating positioning errors and guaranteeing the effectiveness of a robotic walking system. Thus, a simple reliable procedure is proposed as based on a simplified version of Milli-CaTraSys (Milli Cassino Tracking System). Experimental tests are carried out on a biped locomotor that is named as WL-16RII (Waseda Leg No.16 Refined II) in dynamic conditions. The experimental tests provide useful information for both design and control purposes.

This paper describes a passive dynamic model of passenger for a biped walking vehicle. The walking pattern generation that enables stable walking even if passenger sits naturally is also described. The model consists of lower-timbs part assumed to be fixed to the robot, and the upper body assumed to be 1 particle with 2 DOF mounted on the seat via 2 springs and dampers. The parameters are identified through waist shaking experiments by using a force-torque sensor under the seat. The walking pattern generation method involves the proposed model being built onto a strict model of the robot, and through iteration computation, a stable walking pattern is generated. The effectiveness of the proposed method is confirmed through experiments.

Many researchers have been studying on walking control methods for biped robots. However, the effectiveness of these control methods was not verified in outdoor environments such as pedestrian roads and gravel roads. In this paper, a landing pattern modification method adaptable to uneven terrain in a real environment is proposed which is based on a predictive attitude compensation control and a nonlinear compliance control. This method does not require any other sensors except force sensors. Also, a new biped foot system is described which can form larger support polygons on uneven terrain than conventional biped foot systems. Using the modification method and the foot system, NNIL-16RII (Waseda Leg - No.16 Refined II) achieved a stable walk on bumpy terrain with 20 mm height and 10 degrees inclination. Furthermore, a stable dynamic walk was realized on a paved road, when a human rode it. Through various walking experiments, the effectiveness of the method was confirmed.

This paper describes the development of the prototype of the biped walking wheelchair. This robot WL-16RII consists of two Stewart Platform type legs and waist with passenger seat. The walking control method based on ZMP criteria and virtual compliance control for this robot were also developed. Through various experiments, the effectiveness of developed hardware and control method was confirmed.

Many researchers have been studied on acceleration control algorithms for biped robots to deal with uneven terrain. However, the control algorithms are difficult to be used for human-carrying biped walking robots because of modeling errors. In this paper, a landing pattern modification method is proposed which based on nonlinear compliance control. Theoretical compliance displacements calculated from a walking pattern are compared with the actual compliance displacements, while a robot's foot touches slightly uneven terrain. In result, the height of landing terrain is detected, and the preset walking pattern is modified. Using this method, a human-carrying biped robot will be able to walk stably on uneven terrain. This pattern modification method does not need any special sensors except force sensors. Through various walking experiments, the effectiveness of the method is confirmed.

This paper describes one method to stop suddenly and safely avoid failing using only hardware and without a computer system. This method consists of attaching a braking function to leg actuators and the development of a fall avoidance mechanism, attached to the robot's foot. Using the human-carrying biped locomotor NVL-16RII (Figure 1) developed by Sugabara et al., the effectiveness of the method proposed in this paper was confirmed through an emergency stopping experiment during walking, while carrying a heavy load.

This paper describes the development of a prototype biped walking wheelchair. This robot consists of two Stewart Platform type legs and waist with a passenger seat. The walking control method based on ZMP criteria and virtual compliance control method for this robot were also developed. Through various experiments, the effectiveness of the developed hardware and the control method was confirmed.

To date, many control methods have been researched on the assumption that the soles of a biped walking robot contact the ground as four points. It is difficult for almost all biped robots to maintain four-point-contact on uneven terrain because they have rigid and flat soles. It means that the biped robots can lose their balance. To solve this kind of problem, not only stability controls but also foot mechanisms should be studied. So, we developed a foot system, WS-1 (Waseda Shoes - No.1) that can maintain four-point-contact on uneven terrain, different from conventional foot systems. However, since WS-1 has some problems, an improved foot system, WS-1R (Waseda Shoes - No.1 Refined) is developed. Through hardware experiments, the effectiveness of WS-1R is confirmed.

This paper describes the means of tuning-up method of the walking parameters to go up and down stairs for a biped robot with leg mechanisms using Stewart Platforms. It has been confirmed that the stroke range of use could be reduced by tuning up the waist yaw trajectory and preset ZMP trajectories for motion pattern generation. By using the developed method, a walking experiment involving movement up and down a stair with the rise of 250 mm and certain walking experiments ascending and descending stairs carrying a human were successfully completed. Through these experiments, the effectiveness of the proposed method was confirmed.

To date, many control methods have been studied, assuming that the soles of a biped walking robot contact the ground as four points. It is difficult for a biped robot with rigid and flat soles to maintain four-point contact on uneven terrain. It means that the biped robot can lose its balance. To solve this kind of problem, we should study not only stability control methods but also foot mechanisms. In this paper, a new foot system, WS-1 (Waseda Shoes - No.1), is proposed to maintain four-point contact. This foot system consists of cam-type locking mechanism. WS-1 is attached to the feet of WL-16 (Waseda Leg - No.16) that is the world's first biped-walking robot capable of carrying a human. Through hardware experiments, the effectiveness of the foot system is confirmed.

This paper describes a walking control method on inclined planes for a biped locomotor. The walking control consists of a position control, virtual compliance control and posture control. Parameters of the compliance control are changed continuously in support and swing phases. The orientation of robot's waist is kept level by posture control. Several walking experiments on inclined planes are conducted using WL-16R (Waseda Leg - No.16 Refined). WL-16R has achieved stable walking on unknown inclined planes using the walking control method, and the effectiveness of the walking control is confirmed.

Biped walking is easily adaptable to rough terrain such as stairs and stony paths, but the walk speed and energy efficiency on the flat ground is not so effective compared with wheeled locomotion. In this paper, we propose a biped robot to be able to walk or wheel according to the ground conditions. For wheeled locomotion, WS-2 (Waseda Shoes - No.2) is developed which is composed of a DC motor, a spherical caster and two rubber pads on each foot. WS-2 is attached to the feet of WL-16 (Waseda Leg - No.16) that is the world's first biped-walking robot capable of carrying a human. Also, a path planning for wheeled locomotion is presented. Through hardware experiments, the effectiveness of this foot module is confirmed.