Policy search for multi-robot coordination under uncertainty
© 2015, MIT Press Journals. All rights reserved. We introduce a principled method for multi-robot coordination based on a generic model (termed a MacDec-POMDP) of multi-robot cooperative planning in the presence of stochasticity, uncertain sensing and communication limitations. We present a new MacDec-POMDP planning algorithm that searches over policies represented as finite-state controllers, rather than the existing policy tree representation. Finite-state controllers can be much more concise than trees, are much easier to interpret, and can operate over an infinite horizon. The resulting policy search algorithm requires a substantially simpler simulator that models only the outcomes of executing a given set of motor controllers, not the details of the executions themselves and can to solve significantly larger problems than existing MacDec-POMDP planners. We demonstrate significantly improved performance over previous methods and application to a cooperative multi-robot bartending task, showing that our method can be used for actual multi-robot systems.
Amato, C; Konidaris, G; Anders, A; Cruz, G; How, JP; Kaelbling, LP
Volume / Issue
Electronic International Standard Serial Number (EISSN)
International Standard Book Number 13 (ISBN-13)
Digital Object Identifier (DOI)