Multi Robot Navigation

Multi-robot navigation focuses on coordinating multiple robots to achieve a common goal, such as exploration or delivery, while avoiding collisions and optimizing efficiency. Current research emphasizes decentralized approaches, often employing reinforcement learning (particularly distributional RL), artificial potential fields, and graph neural networks to enable robots to navigate dynamically without relying on centralized control or extensive communication. These advancements are crucial for applications ranging from disaster response and warehouse automation to autonomous driving in unstructured environments, improving efficiency and robustness in complex scenarios.