Abstract
An autonomous robot team can be employed for continuous and strategic coverage of arbitrary environments for different missions. In this work, we propose an anytime approach for creating multi-robot patrolling policies. Our approach involves a novel extension of Monte Carlo Tree Search (MCTS) to allow robots to have life-long, cyclic policies so as to provide continual coverage of an environment. Our proposed method can generate near-optimal policies for a team of robots for small environments in real-time (and in larger environments in under a minute). By incorporating additional planning heuristics we are able to plan coordinated patrolling paths for teams of several robots in large environments quickly on commodity hardware.
Original language | English (US) |
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Article number | 7139357 |
Pages (from-to) | 1289-1294 |
Number of pages | 6 |
Journal | Proceedings - IEEE International Conference on Robotics and Automation |
Volume | 2015-June |
Issue number | June |
DOIs | |
State | Published - Jun 29 2015 |
Event | 2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States Duration: May 26 2015 → May 30 2015 |