Portal de Periódicos da CAPES

Policy search for multi-robot coordination under uncertainty

2016; SAGE Publishing; Volume: 35; Issue: 14 Linguagem: Inglês

10.1177/0278364916679611

1741-3176

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

Robotic Path Planning Algorithms

We introduce a principled method for multi-robot coordination based on a general model (termed a MacDec-POMDP) of multi-robot cooperative planning in the presence of stochasticity, uncertain sensing, and communication limitations. A new MacDec-POMDP planning algorithm is presented that searches over policies represented as finite-state controllers, rather than the previous 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 solve significantly larger problems than existing MacDec-POMDP planners. We demonstrate significant performance improvements over previous methods and show that our method can be used for actual multi-robot systems through experiments on a cooperative multi-robot bartending domain.