IROS 2015 Paper Abstract


Paper ThAP.53

Tan, Jeffrey Too Chuan (University of Tokyo), Hagiwara, Yoshinobu (National Institute of Infomatics), Inamura, Tetsunari (National Institute of Informatics)

Crowdsourcing of Virtual Human-Robot Interaction for Robot Learning of Collaborative Actions and Communication Behaviors

Scheduled for presentation during the Poster session "Late Breaking Posters" (ThAP), Thursday, October 1, 2015, 09:45−10:00, Saal G1

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept 28 - Oct 03, 2015, Congress Center Hamburg, Hamburg, Germany

This information is tentative and subject to change. Compiled on July 19, 2019

Keywords Human-Robot Interaction, Robot Learning, Virtual Reality and Interfaces


In this work, we propose a virtual human-robot interaction system that enables crowdsourcing, in order to collect a large group of learning data in a much shorter time and cost needed. There are several related game based developments with similar crowdsourcing concept, but the robot behaviors in term of the coordination between physical actions and communication are loosely discussed. The objective of this work is to improve the robot learning to include the coordination between action and communication. Apart from learning the physical actions, we are also investigating the information flow during the collaboration. A cloud based virtual environment is developed with human-robot collaborative task scenario for the implementation of crowdsourcing human-robot interaction for robot learning.



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