Multi-Policy Decision Making (MPDM) has been shown to be an effective method for single-agent navigation tasks. In this paper, we extend MDPM to long-horizon multi-robot planning tasks with uncertain communication. We constrain each team member to choose the best of several simple policies through forward simulation in a decentralized fashion. We demonstrate this algorithm on both a coverage task as well as a challenging adversarial target search scenario, with uncertain communication for both. We also show that our algorithm can generalize to scenarios it was not tuned for.
@misc{krogius2020iros, TITLE = {Decentralized Multi-Policy Decision Making for Communication Constrained Multi-Robot Coordination (Preprint)}, AUTHOR = {Maximilian Krogius and Acshi Haggenmiller and Edwin Olson}, BOOKTITLE = {Preprint}, YEAR = {2021}, MONTH = {May}, KEYWORDS = {Planning, Search and Rescue, Multi-robot, Decentralized}, }