MORI, Hiroki

写真a

Affiliation

Research Council (Research Organization), Future Robotics Organization

Job title

Researcher(Associate Professor)

Concurrent Post 【 display / non-display

  • Faculty of Science and Engineering   School of Fundamental Science and Engineering

Education 【 display / non-display

  • 2006.04
    -
    2009.09

    The University of Tokyo   Faculty of Information Science and Technology   Department of Mechano-Informatics  

  • 2004.04
    -
    2006.03

    Toyohashi University of Technology   Graduate School of Engineering   Department of Computer Science and Engineering  

  • 2002.04
    -
    2004.03

    Toyohashi University of Technology   Faculty of Engineering   Department of Computer Science and Engineering  

  • 1997.04
    -
    2002.03

    Gifu National College of Technology   Department of Electrical Engineering  

Degree 【 display / non-display

  • University of Tokyo   Ph.D

Research Experience 【 display / non-display

  • 2017.10
    -
    Now

    Waseda University   Future Robotics Organization   Researcher/Associate Professor

  • 2017.04
    -
    2017.09

    Waseda University   Ogata Laboratory, Faculty of Science and Engineering   Assistant Professor

  • 2017.04
    -
    2017.09

    Waseda University   Future robotics organization   Junior Researcher

  • 2016.04
    -
    2017.03

    University of Cergy-Pontoise (Frande)   ETIS lab   Researcher

  • 2011.04
    -
    2016.03

    Osaka University   Department of Adaptive Machine Systems, Graduate School of Engineering   Assistant Professor

display all >>

Professional Memberships 【 display / non-display

  • 2020.08
    -
    Now

    The Japanese Society for Artificial Intelligence

  •  
     
     

    The Japanese society of baby science

  •  
     
     

    THE INSTITUTE OF ELECTRICAL ENGINEERS OF JAPAN

  •  
     
     

    Japan Society for Developmental Neuroscience

  •  
     
     

    THE ROBOTICS SOCIETY OF JAPAN

 

Research Areas 【 display / non-display

  • Embryonic medicine and pediatrics   Developmental Science

  • Neuroscience-general   Computational Neuroscience

  • Intelligent robotics

Research Interests 【 display / non-display

  • Motion analysis

  • infant

  • consciousness

  • development

  • fetus

display all >>

Papers 【 display / non-display

  • Macroscopic Cluster Organizations Change the Complexity of Neural Activity

    Jihoon Park, Koki Ichinose, Yuji Kawai, Junichi Suzuki, Minoru Asada, Hiroki Mori

    Entropy   21 ( 2 ) 214  2019.02  [Refereed]

    DOI

  • Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks

    Jihoon Park, Hiroki Mori, Yuji Okuyama, Minoru Asada

    PLOS ONE   12 ( 8 ) e0182518  2017.08  [Refereed]

     View Summary

    Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the "information networks" different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed.

    DOI

  • A human fetus development simulation: Self-organization of behaviors through tactile sensation

    Hiroki Mori, Yasuo Kuniyoshi

    2010 IEEE 9th International Conference on Development and Learning, ICDL-2010 - Conference Program   vol. 9   82 - 87  2010  [Refereed]

     View Summary

    Recent progresses of ultrasound imaging technology have led observations of fetal intrauterine behavior and a perspective of intrauterine learning. Understanding fetal behavior in uterus is important for medical cares for prenatal infants, because the intervention like "nesting" or "swaddling" in NICU (Neonatal Intensive Care Unit) is based on a perspective of intrauterine learning. However, fetal behavior is not explained sufficiently by the perspective. In this study, we have proposed a hypothesis in which two fetal behaviors, Isolated leg/arm movements and hand and face contact, emerge within self-organization of interaction among an uterine environment, a fetal body, and a nervous system. through tactile sensation in uterus. We have conducted computer experiments with a simple musculoskeletal model in uterus and a whole body fetal musculoskeletal model with tactile for the hypothesis. We confirmed that tactile sensation induces motions in the experiments of the simple model, and the fetal model with human like tactile distribution have behaved with the two motions similar to real fetal behaviors. Our experiments indicated that fetal intrauterine learning is possibly core concept for the fetal motor development. © 2010 IEEE.

    DOI

  • A Developmental Nervous System Model for Fetal Reflexive Behaviorswhich are Self-organized via Tactile Sensation

    森裕紀, 國吉康夫

    日本ロボット学会誌   28 ( 8 ) 1014 - 1024  2010  [Refereed]

    DOI

  • Tool-Use Model to Reproduce the Goal Situations Considering Relationship Among Tools, Objects, Actions and Effects Using Multimodal Deep Neural Networks

    Namiko Saito, Tetsuya Ogata, Hiroki Mori, Shingo Murata, Shigeki Sugano

    Frontiers in Robotics and AI   8  2021.09  [Refereed]  [International journal]

     View Summary

    We propose a tool-use model that enables a robot to act toward a provided goal. It is important to consider features of the four factors; tools, objects actions, and effects at the same time because they are related to each other and one factor can influence the others. The tool-use model is constructed with deep neural networks (DNNs) using multimodal sensorimotor data; image, force, and joint angle information. To allow the robot to learn tool-use, we collect training data by controlling the robot to perform various object operations using several tools with multiple actions that leads different effects. Then the tool-use model is thereby trained and learns sensorimotor coordination and acquires relationships among tools, objects, actions and effects in its latent space. We can give the robot a task goal by providing an image showing the target placement and orientation of the object. Using the goal image with the tool-use model, the robot detects the features of tools and objects, and determines how to act to reproduce the target effects automatically. Then the robot generates actions adjusting to the real time situations even though the tools and objects are unknown and more complicated than trained ones.

    DOI

display all >>

Industrial Property Rights 【 display / non-display

Awards 【 display / non-display

  • IEEE International Conference on Robotics and Automation (ICRA) 2021 Best Paper Award in Cognitive Robotics

    2021.06   Robotics and Automation Society of IEEE   How to select and use tools? : Active Perception of Target Objects Using Multimodal Deep Learning

    Winner: Namiko Saito, Tetsuya Ogata, Satoshi Funabashi, Hiroki Mori, Shigeki Sugano

     View Summary

    Selection of appropriate tools and use of them when performing daily tasks is a critical function for introducing robots for domestic applications. In previous studies, however, adaptability to target objects was limited, making it difficult to accordingly change tools and adjust actions. To manipulate various objects with tools, robots must both understand tool functions and recognize object characteristics to discern a tool– object–action relation. We focus on active perception using multimodal sensorimotor data while a robot interacts with objects, and allow the robot to recognize their extrinsic and intrinsic characteristics. We construct a deep neural networks (DNN) model that learns to recognize object characteristics, acquires tool–object–action relations, and generates motions for tool selection and handling. As an example tool-use situation, the robot performs an ingredients transfer task, using a turner or ladle to transfer an ingredient from a pot to a bowl. The results confirm that the robot recognizes object characteristics and servings even when the target ingredients are unknown. We also examine the contributions of images, force, and tactile data and show that learning a variety of multimodal information results in rich perception for tool use.

  • JSAI Incentive Award

    2020.07   Japan Society for Artificial Intelligence   Learning to acquire integrated representations of language, environment, and action: Understanding unknown linguistic commands by retrofitted word embeddings

    Winner: Minori Toyoda, Hiroki Mori, Kanata Suzuki, Yoshihiko Hayashi, Tetsuya Ogata

  • Excellent Presentation Award

    2019.12   System Integration Division, The Society of Instrument and Control Engineers   Development of Automatic Classification System for Jellyfish Sign Using Deep Learning

    Winner: Kosuke Kawano, Naoya Iijima, Nozomi Nanki, Akira Furui, Zu Soh, Hiroki Mori, Hideaki Hayashi, Shinji Kume, Toshio Tsuji

  • Best paper award

    2017.12   50th Annual conference of Chugoku and Shikoku brunch on Japan ergonomics society   Development of Evaluation System for Standing Stability Analysis Using Gaze Tracking Task

    Winner: Nozomi Nanki, Zu Soh, Yasuko Funabiki, Shino Ogawa, Taiko Shiwa, Kazuo Funabiki, Naoki Kinoshita, Katsuaki Kawashima, Akira Furui, Hiroki Mori, Koji Shimatani, Toshio Tsuji

  • 第11回学術集会 最優秀発表賞

    2011.10   日本赤ちゃん学会学術講演会   原始歩行シミュレーション―子宮内経験が導く歩行様運動のための神経回路―

    Winner: 森 裕紀

display all >>

Research Projects 【 display / non-display

  • Revealing the principles of early development and its disorders based on simulation of the fetus and neonate

    Project Year :

    2012.10
    -
    2016.03
     

    Yasuo Kuniyoshi

  • Constructive Developmental Science Based on Understanding the Process from Neuro-Dynamics to Social Interaction

    Project Year :

    2012.04
    -
    2016.03
     

    Minoru Asada

  • Constructive developmental research: Structural of nervous system, body, environment limitation induces human development from a fetus to an infant.

    Project Year :

    2012.04
    -
    2016.03
     

    Hiroki Mori

    Authorship: Principal investigator

  • Development and validation of a fetus and preterm infant robot with soft skin and artificial uterine environemnt

    Project Year :

    2012.04
    -
    2014.03
     

    Hiroki Mori

    Authorship: Principal investigator

  • 構成的手法による身体バブリングから社会性獲得にいたる発達過程の理解と構築

    Project Year :

    2010.04
    -
    2012.03
     

    浅田 稔

 

Syllabus 【 display / non-display

Teaching Experience 【 display / non-display

  • Human-centric mechanism

    Waseda University  

    2020.04
    -
    Now
     

  • Basics of Dynamic Intelligence and Representation System

    Waseda University  

    2019.04
    -
    Now
     

  • Programing practice

    Osaka University  

    2011.10
    -
    2015.03
     

  • 計算機とプログラミング

    大阪大学  

  • 機械力学実験

    大阪大学  

display all >>

 

Committee Memberships 【 display / non-display

  • 2014.09
    -
    Now

    日本ロボット学会  開かれた知能専門委員会

  • 2011.10
    -
    Now

    発達神経科学会  理事会

  • 2011.04
    -
    Now

    日本赤ちゃん学会  若手部会