Dynamic Chess: Strategic Planning for Robot Motion

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1853/38868

Title: Dynamic Chess: Strategic Planning for Robot Motion
Author: Kunz, Tobias ; Kingston, Peter ; Stilman, Mike ; Egerstedt, Magnus B.
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.
Type: Pre-print
URI: http://hdl.handle.net/1853/38868
Citation: T. Kunz, P. Kingston, M. Stilman, and M. Egerstedt. Dynamic Chess: Strategic Planning for Robot Motion. IEEE International Conference on Robotics and Automation, Shanghai, China, May 2011. To appear.
Date: 2011-05
Contributor: Georgia Institute of Technology. School of Electrical and Computer Engineering
Georgia Institute of Technology. Center for Robotics and Intelligent Machines
Publisher: Georgia Institute of Technology
Institute of Electrical and Electronics Engineers
Subject: Human-robot interaction
Hybrid dynamics
Robotic motions

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