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},
}