MAAISep 16, 2024

Multi-agent Path Finding in Continuous Environment

arXiv:2409.10680v11 citationsh-index: 2
Originality Synthesis-oriented
AI Analysis

This addresses path planning for multiple agents in continuous spaces, but it is incremental as it builds on existing CBS and RRT* techniques.

The paper tackles multi-agent path finding in continuous environments by proposing a new algorithm, CE-CBS, which combines conflict-based search with RRT* for path planning, and shows it is competitive with other continuous-time MAPF methods in experiments.

We address a variant of multi-agent path finding in continuous environment (CE-MAPF), where agents move along sets of smooth curves. Collisions between agents are resolved via avoidance in the space domain. A new Continuous Environment Conflict-Based Search (CE-CBS) algorithm is proposed in this work. CE-CBS combines conflict-based search (CBS) for the high-level search framework with RRT* for low-level path planning. The CE-CBS algorithm is tested under various settings on diverse CE-MAPF instances. Experimental results show that CE-CBS is competitive w.r.t. to other algorithms that consider continuous aspect in MAPF such as MAPF with continuous time.

Foundations

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