Decentralized control of Partially Observable Markov Decision Processes using belief space macro-actions
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Author(s)
Omidshafiei, Shayegan
Aghamohammadi, Aliakbar
Amato, Christopher
How, Jonathan P
Date Issued
July 2015
Journal
2015 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Omidshafiei, Shayegan, Ali-akbar Agha-mohammadi, Christopher Amato, and Jonathan P. How. “Decentralized Control of Partially Observable Markov Decision Processes Using Belief Space Macro-Actions.” 2015 IEEE International Conference on Robotics and Automation (ICRA) (May 2015).
Version
Author's final manuscript
Abstract
The focus of this paper is on solving multi-robot planning problems in continuous spaces with partial observability. Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) are general models for multi-robot coordination problems, but representing and solving Dec-POMDPs is often intractable for large problems. To allow for a high-level representation that is natural for multi-robot problems and scalable to large discrete and continuous problems, this paper extends the Dec-POMDP model to the Decentralized Partially Observable Semi-Markov Decision Process (Dec-POSMDP). The Dec-POSMDP formulation allows asynchronous decision-making by the robots, which is crucial in multi-robot domains. We also present an algorithm for solving this Dec-POSMDP which is much more scalable than previous methods since it can incorporate closed-loop belief space macro-actions in planning. These macro-actions are automatically constructed to produce robust solutions. The proposed method's performance is evaluated on a complex multi-robot package delivery problem under uncertainty, showing that our approach can naturally represent multi-robot problems and provide high-quality solutions for large-scale problems.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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DOI of Published Version
https://doi.org/10.1109/ICRA.2015.7140035
