Force sensing is a crucial task for robots, especially when end effectors such as fingers and hands need to interact with unknown environments
to sense such forces, a force-torque (F/T) sensor is an essential component. In this paper, we propose a small-sized 6-axis F/T sensor with a novel arrangement of 12 transducers using the force transducer we have previously developed. The copper beryllium used in our sensor reduces hysteresis in each transducer. Additionally, the sensor provides digital output via I2C bus to reduce the susceptibility to noise, and reduce the number of required wires. Sensor characteristics such as its sensitivity, signal-to-noise ratio, linearity, and hysteresis are determined. More importantly, we showed that our sensor can detect and measure the 6-axis F/T.

Torque limiters are a proven way to enhance the safety in robots. To further increase the safety, adjustable torque limits depending on the task and the joint configuration (joint angles, velocity, acceleration) would be preferable. Friction clutches can be used as adjustable torque limiters (ATL). In contact free motion the ATL can be set with torque limits higher than the required torque, thereby not influencing the position tracking performance. At an impact, the torque is intrinsically limited, enhancing the safety. Furthermore, depending on the implementation, friction clutches have another relevant property. They can have different torque limits for static and kinetic friction: When the static torque limit is exceeded (as it would be the case in an incidental contact situation), the clutch starts slipping, and the torque output automatically decreases, thereby reducing the forces in a quasi-static contact, as defined in ISO/TS 15066:2016. The current paper implements and profiles an ATL, which exhibits a kinetic torque limit of only 50.4% of the static torque limit at 10rpm. This ensures both an adjustable torque limit fitting to the task requirement and a lower but not zero torque after impact for enhanced safety. Impact experiments validate the safety benefits outlined above.

In this paper we present a low-cost and easy to fabricate 3-axis tactile sensor based on magnetic technology. The sensor consists in a small magnet immersed in a silicone body with an Hall-effect sensor placed below to detect changes in the magnetic field caused by displacements of the magnet, generated by an external force applied to the silicone body. The use of a 3-axis Hall-effect sensor allows to detect the three components of the force vector, and the proposed design assures high sensitivity, low hysteresis and good repeatability of the measurement: notably, the minimum sensed force is about 0.007N. All components are cheap and easy to retrieve and to assemble
the fabrication process is described in detail and it can be easily replicated by other researchers. Sensors with different geometries have been fabricated, calibrated and successfully integrated in the hand of the human-friendly robot Vizzy. In addition to the sensor characterization and validation, real world experiments of object manipulation are reported, showing proper detection of both normal and shear forces.

The detection of small forces is of great interest in any robotic application that involves interaction with the environment (e.g., objects manipulation, physical human-robot interaction, minimally invasive surgery), since it allows the robot to detect the contacts early on and to act accordingly. In this letter, we present a sensor design inspired by the ciliary structure frequently found in nature, consisting of an array of permanently magnetized cylinders (cilia) patterned over a giant magnetoresistance sensor (GMR). When these cylinders are deformed in shape due to applied forces, the stray magnetic field variation will change the GMR sensor resistivity, thus enabling the electrical measurement of the applied force. In this letter, we present two 3 mm � 3 mm prototypes composed of an array of five cilia with 1 mm of height and 120 and 200 μm of diameter for each prototype. A minimum force of 333 μ N was measured. A simulation model for determining the magnetized cylinders average stray magnetic field is also presented.

This paper proposes a way to protect endangered wayang puppet theater, an intangible cultural heritage from Indonesia, by turning a robot into a puppeteer successor. We developed a seven degrees-offreedom (DOF) manipulator to actuate the sticks attached to the wayang puppet body and hands. The robot can imitate 8 distinct human puppeteer’smanipulations. Furthermore, we developed a gamelan music pattern recognition, towards a robot that can perform based on the gamelan music. In the offline experiment, we extracted energy (time domain), spectral rolloff, 13 Mel-frequency cepstral coefficients (MFCCs), and the harmonic ratio from 5 s long clips, every 0.025 s, with a window length of 1 s, for a total of 2576 features. Two classifiers (3 layers feed-forward neural network (FNN) and multi-class Support Vector Machine (SVM)) were compared. The SVMclassifier outperformed the FNN classifier with a recognition rate of 96.4%for identifying the three different gamelan music patterns.

<p>This paper proposes a wearable device mounted on a human fingertip which measures the 3-axis force on the fingertip (both normal and shear forces) exerted while grasping or touching. The device consists of two Hall-Effect sensors attached on both sides of the fingertip to measure the finger pad deformation caused by external forces on the palmar side of the finger. The experiments in this paper proved that the device can measure both normal force and shear force. The recorded forces could be used for example to record the forces that human exert while manipulating objects.</p>

<p>Force sensing is a crucial task for robots, especially when the end effectors such as fingers and hands need to interact with an unknown environment. In order to sense such forces, a force/torque sensor is an essential component. Many available force/torque sensors are based on strain gauges, but other sensing principles are also possible. Capacitive sensors have the advantage of the availability of small sized chips for sensor readout and digitization. Therefore, in this paper, we propose a small-sized 6-axis force-torque sensor using a novel arrangement of 12 unit of the transducers based on the capacitive force transducer we have previously developed. The copper beryllium used in our sensor acts as a capacitive transducer. The transducer has a hard limit which makes the sensor robust to overload. Additionally, this sensor provides digital output via I2C bus to reduce the susceptibility to noise, and reduce the number of required wires.</p>

This paper presents an easy means to produce a 3-axis Hall effect-based skin sensor for robotic applications. It uses an off-the-shelf chip and is physically small and provides digital output. Furthermore, the sensor has a soft exterior for safe interactions with the environment; in particular it uses soft silicone with about an 8 mm thickness. Tests were performed to evaluate the drift due to temperature changes, and a compensation using the integral temperature sensor was implemented. Furthermore, the hysteresis and the crosstalk between the 3-axis measurements were evaluated. The sensor is able to detect minimal forces of about 1 gf. The sensor was calibrated and results with total forces up to 1450 gf in the normal and tangential directions of the sensor are presented. The test revealed that the sensor is able to measure the different components of the force vector.

Indoor positioning remains an open problem, because it is difficult to achieve satisfactory accuracy within an indoor environment using current radio-based localization technology. In this study, we investigate the use of Indoor Messaging System (IMES) radio for high-accuracy indoor positioning. A hybrid positioning method combining IMES radio strength information and pedestrian dead reckoning information is proposed in order to improve IMES localization accuracy. For understanding the carrier noise ratio versus distance relation for IMES radio, the signal propagation of IMES radio is modeled and identified. Then, trilateration and extended Kalman filtering methods using the radio propagation model are developed for position estimation. These methods are evaluated through robot localization and pedestrian localization experiments. The experimental results show that the proposed hybrid positioning method achieved average estimation errors of 217 and 1846 mm in robot localization and pedestrian localization, respectively. In addition, in order to examine the reason for the positioning accuracy of pedestrian localization being much lower than that of robot localization, the influence of the human body on the radio propagation is experimentally evaluated. The result suggests that the influence of the human body can be modeled.

Human's ability to perceive intent plays a crucial role in achieving smooth and efficient navigation. At the present state, even with the state-of-the-art anthropomorphic robots, displaying human-like non-verbal communication (kinesics) is a challenging task. This poses a significant difficulty in performing legible navigation behavior for robots. In this paper, we look into light (turn indicator) and screen (arrow indicator) indicators as a means of overcoming the shortcomings of the robot's non-verbal communication abilities. Our results show a statistically significant improvement in perceived comfort, predictability, and performance with the use of light indicators.

This paper presents a low cost, easy to produce, small tactile sensor system, that can be embedded in a soft material and limited space. In the current implementation, we use a Hall-effect sensor and a magnet to measure the force. One sensor module can measure 3D force vector and temperature. This chip is planted inside a 55 x 55 x 8 mm of the silicon layer. The module has I2C digital output, requiring only four wires for each module. The experiment shows that the signal to noise ratio (SNR) for this module is relatively high, 21.4658 dB when 20g load is applied. The experiment also indicates that the sensor module measured loads differently depending on the type of material that is in contact.

Human's ability to perceive intent plays a crucial role in achieving smooth and efficient navigation. At the present state, even with the state-of-the-art anthropomorphic robots, displaying human-like non-verbal communication (kinesics) is a challenging task. This poses a significant difficulty in performing legible navigation behavior for robots. In this paper, we look into light (turn indicator) and screen (arrow indicator) indicators as a means of overcoming the shortcomings of the robot's non-verbal communication abilities. Our results show a statistically significant improvement in perceived comfort, predictability, and performance with the use of light indicators.

Legible robot behavior is a key element for smooth and efficient navigation among humans. However, at present, even the state-of-the-art robots cannot communicate its internal state of directional intent by displaying human-like non-verbal cues. In this paper, we explore various modes for communicating directional intent of a robot across three different scenarios as a means of overcoming the shortcomings of the robot's non-verbal communication abilities. Specifically, we look into turn indicators, display indicators, and their combinations with sound and investigate their effectiveness across different passing scenarios. Our study shows us that using auxiliary communicating methods significantly improves the perceived feelings of our dependent measures. Further, communicating intention also helps in improving cooperation. However, the effectiveness greatly varies with the modes and the passing scenarios. In the case of 90 degrees crossing scenario, even though participants have positive perceived feelings, this does not necessarily translate into smooth and efficient navigation.

This study aims to develop a fingertip in order to improve the manipulation performance of posture interpolation control for a multifingered robot hand.Increasing the contact area between the fingertips and object is one solution for improving grasping and manipulation stability.A reasonable fingertip shape design and material selection can increase the contact area.In this paper, we compare an anthropomorphic shape to a cylindrical body with a semispherical tip.In order to test the practical property such as contact area size of our proposed fingertip, a pressure experiment was conducted for comparing the two fingertip shapes under different workloads. Finally, we installed the fingertips on a commercial available robot hand Allegro Hand.Two tasks were conducted for evaluating our proposed fingertip with posture interpolation control. The results show that our proposed fingertip could improve manipulation performance by comparing the success rate in both the experiments.

In-hand manipulation is often needed to accomplish a practical task after grasping an object. In-hand manipulation of variously sized and shaped objects in multi-fingered hands without dropping the object is challenging. In this paper we suggest a combined strategy of force control and passive adaptation through soft fingertips with simple interpolation control to achieve in-hand manipulation between various postures and with various objects. While passive compliance can be achieved in numerous ways, this paper uses soft skin, as it does not require complex mechanisms and was easy to integrate in the robot hand (Allegro hand). Softness has proven to significantly ease object grasping, and the current paper shows the importance of softness also for in-hand manipulation. In particular, the simple interpolation strategy between various postures is successful when combined with soft fingertips, with or without force control, but fails with hard fingertips. Objects of varying size, shape and hardness were reliably manipulated. While the soft fingertips enabled good results in our experiments, a sufficiently precise definition of the postures and object size was required. When combining the interpolation control with a force control strategy, bigger errors in defining the posture and object size are possible, without deforming or dropping the object, and the resultant force is lower. As a result, we achieved robust in -hand manipulation between various postures and with objects of different size, shape and hardness.

The advantages of mechanical compliance have driven the development of devices using new smart materials. A new kind of magnetorheological piston based on a toroidal array of magnetorheological valves, has been previously tested to prove its feasibility. However, being an initial prototype its potential was still limited by its complex design, and low output force. This study presents the revisions done to the design with several improvements targeting key performance parameters. An improved annular piston design is also introduced as comparison with conventional devices. The toroidal and annular piston head prototypes are built and tested, and their force performance compared with the previous iteration. The experimental results show an overall performance improvement of the toroidal assembly. However, the force model used in the study still fails to accurately predict the magnetic flux at the gaps of the piston head. This deviation is later verify and corrected using a FEM analysis. The force performance of the new toroidal assembly is on par with the commonplace annular design. It also displays a more linear behaviour, at the expense of lower energy efficiency. Finally, it also shows potential for a greater degree of customisation to meet different system requirements.

A combined method of Doppler positioning and carrier-based hyperbolic positioning with a multi-channel GPS-pseudolite is proposed for indoor localization. This method uses carrier-phase output from a GPS/pseudolite receiver. The carrier-phase observable is precise but does not provide range information between the pseudolite and receiver antennas necessary for position calculation. This is because of the existence of carrier ambiguity. This problem can be solved by using the proposed combined method. In the present work, the positioning theory is established and experimentally evaluated with actual devices including a robot. The experimental result shows that a positioning accuracy of more than 10 cm is achievable.

Integrating distributed sensors in the skin of robot hands is challenging, as the space is limited. This paper presents a dense and small tactile sensor system that can be installed on robotic hands. In the current implementation, the system is constituted by modules that are 26mm long and 27mm wide and they have been successfully integrated on the internal side of each finger phalange of the commercially available Allegro Hand (except the fingertips). Each sensor module contains 16 tri-axial taxels; each taxel is able to measure the applied 3D force vector using a Hall effect sensor and a magnet. The sensor modules are 4mm high, including the printed circuit board (PCB) with the sensors and the soft silicone with the magnets. The back of the PCB is flat without any components mounted, which eases the integration. Each sensor has I2C digital output, and each sensor module is connected to four I2C buses, requiring only seven wires for each module. The tri-axial taxels are close to each other (4.7 mm from the center of one taxel to the next), but experiments proved that independent force vectors can be measured and that the crosstalk is limited.

This research aims to clarify and analyze potential factors in fingertip designs and conditions which may affect prehension performances in addition to the control strategy. In this paper, four factors of fingertip designs and conditions are considered: hardness, thickness of the skin, shape and the surface friction condition of the fingertip. Six fingertips were made in order to compare these factors and their influences on grasp stability under different conditions (high and low workload). An evaluation experiment was conducted in order to investigate how the proposed properties affect the grasping performance under different workloads. Results show an unexpected effectiveness of the soft skin grasping performance compared to less deformable materials, even with reduced friction; also the orientation of the fingertips significantly affects the grasping performance in the case of anthropomorphic fingertips. These results can be useful for designing a new robot hand and a control strategy, which can potentially lead to a better stability and efficient performance.

Moving objects within the hand is challenging, especially if the objects are of various shape and size. In this paper we use machine learning to learn in-hand manipulation of such various sized and shaped objects. The TWENDY-ONE hand is used, which has various properties that makes it well suited for in-hand manipulation: a high number of actuated joints, passive degrees of freedom and soft skin, six-axis force/torque (F/T) sensors in each fingertip, and distributed tactile sensors in the skin. A dataglove is used to gather training samples for teaching the required behavior. The object size information is extracted from the initial grasping posture. After training a neural network, the robot is able to manipulate objects of untrained sizes and shape. The results show the importance of size and tactile information. Compared to interpolation control, the adaptability for the initial posture gap could be greatly extended. Final results show that with deep learning the number of required training sets can be drastically reduced.

This article presents feature extraction with deep learning for in-hand manipulation. It is important that robot hands can manipulate different sized and shaped objects. In order to generate versatile manipulation with such objects, we used deep learning to extract critical information from object manipulating motions.

This paper introduces a novel tri-axial capacitive force sensor. The sensor can measure the force vector, is embedded in soft 7mm-thick silicone skin, enables temperature sensitivity compensation and has digital output. To measure the force vector, tilted capacitive sensor elements are used which are facing in different directions to differentiate the tangential forces. The sensor is intended for distributed contact sensing in a robotic skin, but could be also used for other applications such as novel haptic user interfaces in wearable devices. A series of experiments was performed and showed good sensor characteristics. The concept of the tilted force transducers has been proven to have the capability of detecting the force vector acting on the local sensor surface.

A hyperbolic positioning method with antenna arrays consisting of proximately-located antennas and a multi-channel pseudolite is proposed in order to overcome the problems of indoor positioning with conventional pseudolites (ground-based GPS transmitters). A two-dimensional positioning experiment using actual devices is conducted. The experimental result shows that the positioning accuracy varies centimeter- to meter-level according to the geometric relation between the pseudolite antennas and the receiver. It also shows that the bias error of the carrier-phase difference observables is more serious than their random error. Based on the size of the bias error of carrier-phase difference that is inverse-calculated from the experimental result, three-dimensional positioning performance is evaluated by computer simulation. In addition, in the three-dimensional positioning scenario, an initial value convergence analysis of the non-linear least squares is conducted. Its result shows that initial values that can converge to a right position exist at least under the proposed antenna setup. The simulated values and evaluation methods introduced in this work can be applied to various antenna setups; therefore, by using them, positioning performance can be predicted in advance of installing an actual system.

This paper describes a combined tactile sensor and haptic interface that can change its stiffness using magnetorheological fluids (MR fluid). The tactile sensor consists of 6 distributed capacitive sensors that can sense the location and the amount of applied force. Above the sensors is a chamber filled with MR fluid. By changing the magnetic field, the hardness of the MR fluid, and thereby of the haptic interface, can be changed. Fast changes of the magnetization direction lead to a sensation of vibration. The resulting device can be used for novel haptic input devices or for robotic grippers. A prototype device has been constructed, and the effects of the varying magnetic field and the resulting varying stiffness of the MR fluid on the distributed force sensing with the capacitive sensors has been evaluated. We discovered that the measured forces vary very little with changes in the strength of the magnetic field.

This paper proposes a new soft capacitive-type 3-axis force sensor. The prototype version which can detect a multi-axis force vector is embedded inside 7mm-thick silicone skin, and provides digital output via an I2C bus. Tilted capacitive force transducers were used to measure the force vector; the transducers faced different directions to differentiate the tangential forces. Preliminary experiments were performed and the concept of the tilted force transducers has been proven to have the capability of differentiating the force vector acting on the sensor surface. (c) 2015 The Authors. Published by Elsevier B. V.

Passive compliance is useful for robotic arms to ensure their safety. Often springs are used, but they are problematic because they reduce the achievable accelerations and can lead to underdamped oscillations. Torque limiters enhance the safety, but usually the torque limit cannot be adjusted to a desired torque. Electronically adjustable torque limiters, also known as series clutch actuators, have several benefits, especially for robotic arms, but they also have severe limitations. This paper suggests incorporating series clutch actuators into a gravity compensated arm. Consequently, gravity should not limit the isotropically achievable force anymore and in the case of power outage the arm keeps its position. The benefits and limitations of a series clutch actuator in a gravity compensated arm are discussed, and a prototype of such an arm is presented. Commercially available magnetic friction clutches are used. Preliminary experiments demonstrate that the safety can be increased.

As robots progressively continue to enter human lives, it becomes important for robots to navigate safely and efficiently in crowded environments. In fact, efficient navigation in crowded areas is an important prerequisite for successful coexistence between humans and robots. In this paper, we explore an unconventional idea wherein a robot tries to achieve a more efficient navigation by influencing an obstructing human to move away by means of contact. First, preliminary human reaction experiments were conducted wherein we established that we can successfully induce a human to move in a desired direction. Following this result, we have proposed a novel motion planning approach which considers inducement by contact. The system is then verified through simulation and real experiments. The results show us that the proposed method can be utilized for safer and more efficient navigation in a crowded, but relatively static environment.

In this paper we introduce a prototype of a novel hall-effect based skin sensor for robotic applications. It uses a small sized chip that provides 3-axis digital output in a compact package. Our purpose was to evaluate the feasibility of measuring 3-axis force while maintain a soft exterior for safe interactions. Silicone was used to produce the soft skin layer with about 8 mm thickness. An MLX90393 chip was installed at the bottom of layer, with a small magnet approximately 5mm above it to measure 3-axial magnetic field data. To evaluate the sensor's performance, an experiment was conducted by measuring normal and shear force when applying total forces of 0.7-14N in the normal and tangential directions of the sensor. The test revealed that the sensor prototype was able to differentiate the components of the force vector, with limited crosstalk. A calibration was performed to convert the measurements of the magnetic field to force values.

In densely populated scenarios with cramped spaces, it is very difficult to achieve safe and efficient navigation without cooperation from humans. One way in which we can seek cooperation from humans is by using contact to influence them to give way. However, such a method may incur certain psychological implications and therefore requires an acceptability check to ensure whether such action is acceptable or not. For this purpose, we investigate the participant subjective response towards robot-initiated touch during the course of navigation. We conducted a 2 (robotic experience vs. none) x 2 (warning vs. none) between-subject experiment with 44 people in which a mobile robotic platform exerted contact on an unaware and obstructing participant to make way towards its goal. Our results show that prior experience with robots produces slightly better response even though the results are not statistically significant. However, a verbal warning prior to contact yielded much more favorable response. In general, the participants did not find contact to be uncomfortable and were not opposed to robot-initiated contact if deemed necessary.

Object handling and manipulation are important functions of dexterous anthropomorphic hands. As it is difficult to create a manipulation model analytically for performing complex tasks as humans do, a simple way to accomplish generic in-hand manipulation is desirable for robotic hands, especially for robot hands with few sensors. In this paper, we designed standard grasping postures based on the grasping behavior of humans. Interpolation control is used to control the robot hand. The combination of these postures results in versatile object manipulation. This control strategy is evaluated by testing it with the 16 degrees of freedom Allegro Hand grasping different sizes of spheres.

IMES is an indoor messaging and positioning system. In the present work, three methods for improving the IMES transmitter are proposed based on the result of a radio acquisition analysis: transmission diversity, a variable beamwidth antenna, and a leaky coaxial cable (LCX). The transmission diversity method increases the possibility of signal acquisition in areas with weak signal. A small-sized variable beamwidth antenna is developed to mitigate the multipath interference in narrow spaces. A field experiment with a LCX in an actual train setup is conducted to verify the effect of the LCX for the positioning of moving vehicles. The evaluation results of the proposed methods suggest their potential to be applied to practical applications.

Recognizing grasped objects with tactile sensors is beneficial in many situations, as other sensor information like vision is not always reliable. In this paper, we aim for multimodal object recognition by power grasping of objects with an unknown orientation and position relation to the hand. Few robots have the necessary tactile sensors to reliably recognize objects: in this study the multifingered hand of TWENDY-ONE is used, which has distributed skin sensors covering most of the hand, 6 axis F/T sensors in each fingertip, and provides information about the joint angles. Moreover, the hand is compliant. When using tactile sensors, it is not clear what kinds of features are useful for object recognition. Recently, deep learning has shown promising results. Nevertheless, deep learning has rarely been used in robotics and to our best knowledge never for tactile sensing, probably because it is difficult to gather many samples with tactile sensors. Our results show a clear improvement when using a denoising autoencoder with dropout compared to traditional neural networks. Nevertheless, a higher number of layers did not prove to be beneficial.

Force sensing is a crucial task for robots, especially when the end effectors such as fingers and hands need to interact with an unknown environment, for example in a humanoid robot. In order to sense such forces, a force/torque sensor is an essential component. Many available force/torque sensors are based on strain gauges, but other sensing principles are also possible. In this paper we describe steps towards a capacitive type based sensor. Several MEMS capacitive sensors are described in the literature; however very few larger sensors are available, as capacitive sensors usually have disadvantages such as severe hysteresis and temperature sensitivity. On the other hand, capacitive sensors have the advantage of the availability of small sized chips for sensor readout and digitization. We employ copper beryllium for the transducer, which has been modified from the ones described in the literature to be able to be used in a small sized, robust force/torque sensor. Therefore, as the first step toward the goal of building such a sensor, in this study we have created a prototype sensing unit and have tested its sensitivity. No viscoelastic materials are used for the sensing unit, which usually introduce severe hysteresis in capacitive sensors. We have achieved a high signal-to-noise ratio, high sensitivity and a range of 10 Newton.

Handling objects with a single hand without dropping the object is challenging for a robot. A possible way to aid the motion planning is the prediction of the sensory results of different motions. Sequences of different movements can be performed as an offline simulation, and using the predicted sensory results, it can be evaluated whether the desired goal is achieved. In particular, the task in this paper is to roll a sphere between the fingertips of the dexterous hand of the humanoid robot TWENDY-ONE. First, a forward model for the prediction of the touch state resulting from the in-hand manipulation is developed. As it is difficult to create such a model analytically, the model is obtained through machine learning. To get real world training data, a dataglove is used to control the robot in a master-slave way. The learned model was able to accurately predict the course of the touch state while performing successful and unsuccessful in-hand manipulations. In a second step, it is shown that this simulated sequence of sensor states can be used as input for a stability assessment model. This model can accurately predict whether a grasp is stable or whether it results in dropping the object. In a final step, a more powerful grasp stability evaluator is introduced, which works for our task regardless of the sphere diameter.

This article describes the hardware design of the iCub humanoid robot. The iCub is an open-source humanoid robotic platform designed explicitly to support research in embodied cognition. This paper covers the mechanical and electronic design of the first release of the robot. A series upgrades developed for the second version of the robot (iCub2), which are aimed at the improvement of the mechanical and sensing performance, are also described.

Even though the sense of touch is crucial for humans, most humanoid robots lack tactile sensing. While a large number of sensing technologies exist, it is not trivial to incorporate them into a robot. We have developed a compliant "skin" for humanoids that integrates a distributed pressure sensor based on capacitive technology. The skin is modular and can be deployed on nonflat surfaces. Eachmodule scans locally a limited number of tactile-sensing elements and sends the data through a serial bus. This is a critical advantage as it reduces the number of wires. The resulting system is compact and has been successfully integrated into three different humanoid robots. We have performed tests that show that the sensor has favorable characteristics and implemented algorithms to compensate the hysteresis and drift of the sensor. Experiments with the humanoid robot iCub prove that the sensors can be used to grasp unmodeled, fragile objects.

Humanoid robots use tactile fingertips to perform object manipulation. In this paper, an improved prototype of a tactile capacitive fingertip for the hands of the humanoid robot iCub is presented. In particular, a conductive silicone based material has been used to improve the characteristics of the capacitive sensor and an additional silicone foam layer has been also introduced in the sensor architecture to prevent behavior variation due to fingertip deterioration (e.g., caused by object manipulation). A characterization of the fingertip sensing behavior is presented. This work is funded by the European Commission as part of the project ICT-FP7-231500 RoboSKIN.

In order to successfully perform object manipulation, humanoid robots must be equipped with tactile sensors. However, the limited space that is available in robotic fingers imposes severe design constraints. In [1] we presented a small prototype fingertip which incorporates a capacitive pressure system. This paper shows an improved version, which has been integrated on the hand of the humanoid robot iCub. The fingertip is 14.5 mm long and 13 mm wide. The capacitive pressure sensor system has 12 sensitive zones and includes the electronics to send the 12 measurements over a serial bus with only 4 wires. Each synthetic fingertip is shaped approximately like a human fingertip. Furthermore, an integral part of the capacitive sensor is soft silicone foam, and therefore the fingertip is compliant. We describe the structure of the fingertip, their integration on the humanoid robot iCub and present test results to show the characteristics of the sensor.

The sense of touch is of major importance for object handling. Nevertheless, adequate cutaneous sensors for humanoid robot hands are still missing. Designing such sensors is challenging, because they should not only give reliable measurements and integrate many sensing points into little space, but they should also be compliant and should not obstruct the other functions of the robot. This paper presents a capacitive pressure sensor system with 108 sensitive zones for the hands of the humanoid robot iCub. In particular, the palm has 48 taxels and each of the five fingertips has 12 taxels. The size and the shape of the hand are similar to that of a human child. When designing the sensors, we paid special attention to the integration on the robot. Also the ease and speed of production was an important design factor. Furthermore, the sensor incorporates silicone foam and is therefore compliant. We show the working principle of the sensor, how it has been integrated into the hands, and describe experiments that have been performed to show the characteristics of the sensor.

Tactile feedback is of crucial importance for object manipulation in unknown environments. In this paper we describe the design and realization of a fingertip which includes a capacitive pressure sensor with 12 sensitive zones. It is naturally shaped and its size is small enough so that it can be mounted on the fingers of the humanoid robot iCub. It also embeds the electronic device which performs A/D conversion: This is beneficial for the signal to noise ratio and reduces the number of wires required to connect the fingertip to the robot. The fingertip is made of silicone, which makes its surface and inner structure compliant and flexible. We present preliminary experiments performed with the first prototype.