How can LLMs coordinate robots for efficient task allocation in crowded spaces?
Hyper-SAMARL: Hypergraph-based Coordinated Task Allocation and Socially-aware Navigation for Multi-Robot Systems
September 19, 2024
https://arxiv.org/pdf/2409.11561This research tackles the challenge of coordinating multiple robots to complete tasks in dynamic environments shared with humans. The proposed system, Hyper-SAMARL, uses a hypergraph, a data structure that captures complex relationships, to model the interactions between robots, humans, and points of interest. This allows the system to dynamically adjust task allocation and navigate in a socially-aware manner.
The key relevance to LLM-based multi-agent systems is the use of hypergraphs for modeling complex, dynamic relationships and the successful application of reinforcement learning to train the system, highlighting the potential of such approaches in developing sophisticated multi-agent applications.