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Qualcomm Research
Probabilistic Planning for Decentralized Multi-Robot Systems
Amato, Christopher (University of New Hampshire) | Konidaris, George (Duke University) | Omidshafiei, Shayegan (Massachusetts Institute of Technology) | Agha-mohammadi, Ali-akbar (Qualcomm Research) | How, Jonathan P. (Massachusetts Institute of Technology) | Kaelbling, Leslie P. (Massachusetts Institute of Technology)
Multi-robot systems are an exciting application domain for AI research and Dec-POMDPs, specifically. MacDec-POMDP methods can produce high-quality general solutions for realistic heterogeneous multi-robot coordination problems by automatically generating control and communication policies, given a model. In contrast to most existing multi-robot methods that are specialized to a particular problem class, our approach can synthesize policies that exploit any opportunities for coordination that are present in the problem, while balancing uncertainty, sensor information, and information about other agents.