Robotics: Science and Systems XI

Policy Search for Multi-Robot Coordination under Uncertainty

Christopher Amato, George Konidaris, Ariel Anders, Gabriel Cruz, Jonathan How, Leslie Kaelbling


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.



    AUTHOR    = {Christopher Amato AND George Konidaris AND Ariel Anders AND Gabriel Cruz AND Jonathan How AND Leslie Kaelbling}, 
    TITLE     = {Policy Search for Multi-Robot Coordination under Uncertainty}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2015}, 
    ADDRESS   = {Rome, Italy}, 
    MONTH     = {July},
    DOI       = {10.15607/RSS.2015.XI.007}