LSRP*: Scalable and Anytime Planning for Multi-Agent Path Finding with Asynchronous Actions
LSRP*: Scalable and Anytime Planning for Multi-Agent Path Finding with Asynchronous Actions
This research presents LSRP*, a new anytime planner for multi-agent path finding (MAPF) that operates without assuming synchronized actions. The method improves on the earlier Loosely Synchronized Rule-based Planning (LSRP) algorithm by reducing solution cost and supporting more agents. Tests against baselines show LSRP* can handle up to 25% more agents than LSRP and reduce solution cost by up to 40%, while continuing to improve quality until runtime is exhausted.
The paper introduces LSRP*, an anytime planner for multi-agent path finding that removes the synchronized action assumption and improves upon the prior LSRP method by reducing solution cost and handling more agents in tests with up to 1000 agents.
Source: arXiv Robotics — research abstracts · Read original article ↗
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Reported numbers
robots
≤1,000
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on quality after the initial solution is obtained until the runtime budget depletes. We analyze the properties of LSRP* and test it against several baselines with up to 1000 agents on various maps. LSRP* can handle up to 25% more agents than LSRP and can reduce up to 40% of the solution cost found by LSRP.
Open source S4percent
≤25
View original evidence
on quality after the initial solution is obtained until the runtime budget depletes. We analyze the properties of LSRP* and test it against several baselines with up to 1000 agents on various maps. LSRP* can handle up to 25% more agents than LSRP and can reduce up to 40% of the solution cost found by LSRP.
Open source S4percent
≤40
View original evidence
on quality after the initial solution is obtained until the runtime budget depletes. We analyze the properties of LSRP* and test it against several baselines with up to 1000 agents on various maps. LSRP* can handle up to 25% more agents than LSRP and can reduce up to 40% of the solution cost found by LSRP.
Open source S4
- paper: not_reported
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Automatically extracted; no manual editorial approval recorded.
on quality after the initial solution is obtained until the runtime budget depletes. We analyze the properties of LSRP* and test it against several baselines with up to 1000 agents on various maps. LSRP* can handle up to 25% more agents than LSRP and can reduce up to 40% of the solution cost found by LSRP.
Open source S4
Source：arXiv Robotics — research abstracts · arxiv.org