Multi Robot Coordination

Multi-robot coordination focuses on designing algorithms and architectures that enable groups of robots to collaboratively achieve complex tasks, optimizing efficiency and robustness. Current research emphasizes decentralized approaches using graph neural networks, reinforcement learning, and game theory to handle scalability and uncertainty, often incorporating hierarchical structures or bi-level optimization for improved performance. These advancements are significant for applications ranging from warehouse automation and environmental exploration to search and rescue operations, improving task completion speed, safety, and adaptability in challenging environments.