Dynamic Chess: Strategic Planning for Robot Motion

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dc.contributor.author Kunz, Tobias
dc.contributor.author Kingston, Peter
dc.contributor.author Stilman, Mike
dc.contributor.author Egerstedt, Magnus B.
dc.date.accessioned 2011-05-15T22:00:49Z
dc.date.available 2011-05-15T22:00:49Z
dc.date.issued 2011-05
dc.identifier.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. en_US
dc.identifier.uri http://hdl.handle.net/1853/38868
dc.description.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. en_US
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.subject Human-robot interaction en_US
dc.subject Hybrid dynamics en_US
dc.subject Robotic motions en_US
dc.title Dynamic Chess: Strategic Planning for Robot Motion en_US
dc.type Pre-print en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Electrical and Computer Engineering
dc.contributor.corporatename Georgia Institute of Technology. Center for Robotics and Intelligent Machines
dc.publisher.original Institute of Electrical and Electronics Engineers


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