How can I speed up multi-robot path planning?
Streamlining the Action Dependency Graph Framework: Two Key Enhancements
This paper improves the Action Dependency Graph (ADG) framework, a method for coordinating multiple robots. It simplifies the graph construction by proving "wait" actions are unnecessary and introduces a faster algorithm called Sparse Candidate Partitioning (SCP). This reduces computational overhead and allows robots to react faster to changes, crucial for real-world dynamic environments.
For LLM-based multi-agent systems, SCP offers a more efficient way to manage dependencies between agent actions, particularly relevant as the number of agents increases. Removing wait actions and optimizing dependency calculation could improve responsiveness and resource usage in complex multi-agent interactions driven by LLMs.