How can I make complete real-time multi-agent pathfinding?
Real-Time LaCAM
This paper introduces Real-Time LaCAM, a complete algorithm for Multi-Agent Path Finding (MAPF) that operates under real-time constraints. It incrementally builds a search tree, reusing previous computations and adding constraints to avoid deadlock/livelock, making it suitable for applications like warehouse robotics where planning time is limited.
For LLM-based multi-agent systems, Real-Time LaCAM offers a robust framework for coordinating agent actions in dynamic environments. Its compatibility with learned policies, demonstrated through integration with collision-shield PIBT and models like SSIL, highlights its potential for blending traditional search with learned behaviors in real-time multi-agent scenarios. The constraint-based approach can be viewed as a general mechanism applicable to other windowed MAPF planners and potentially other multi-agent coordination tasks involving LLMs.