ICRA 2011 Paper Abstract

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Paper WeP111.5

Kunz, Tobias (Georgia Tech), Kingston, Peter (Georgia Institute of Technology), Stilman, Mike (Georgia Tech), Egerstedt, Magnus (Georgia Institute of Technology)

Dynamic Chess: Strategic Planning for Robot Motion

Scheduled for presentation during the Regular Sessions "Physical Human-Robot Interaction I" (WeP111), Wednesday, May 11, 2011, 14:40−14:55, Room 5F

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on December 8, 2019

Keywords Motion and Path Planning, Physical Human-Robot Interaction

Abstract

We introduce and experimentally validate a novel algorithmic model for physical human-robot interaction with hybrid dynamics. Our computational solutions are complementary to passive and compliant hardware. We focus on the case where human motion can be predicted. In these cases, the robot can select optimal motions in response to human actions and maximize safety. By representing the domain as a Markov Game, we enable the robot to not only react to the human but also to construct an infinite horizon optimal policy of actions and responses. Experimentally, we apply our model to simulated robot sword defense. Our approach enables a simulated 7-DOF robot arm to block known attacks in any sequence. We generate optimized blocks and apply game theoretic tools to choose the best action for the defender in the presence of an intelligent adversary.

 

 

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