Multi-Robot Coordination
Overview
Multi-robot coordination studies how robots with shared or complementary goals work together in settings such as exploration, transport, warehouses, and aerial-ground missions. Approaches include task allocation and scheduling, joint or distributed motion planning, formation and feedback control, and learned policies that use local observations, communication, or demonstrations. Work increasingly combines these methods with safety constraints, uncertainty-aware replanning, and language or vision models, with evaluation spanning simulation, benchmarks, and physical robot teams. A central challenge is balancing the efficiency and global awareness of centralized planning against the scalability, resilience, and limited communication of decentralized teams, especially when robots or environments differ from those seen in training.
Latest papers
326 papers50 papers in the last four weeks, up 22% on the four weeks before. 0.3% of all new papers.