Multiple Robot

Multiple robot systems research focuses on coordinating teams of robots to achieve complex tasks more efficiently than single robots could. Current research emphasizes developing algorithms for collision avoidance, optimal path planning (often using techniques like model predictive control and reinforcement learning), and efficient task allocation, particularly in challenging environments like cluttered spaces or those requiring long-duration autonomy. These advancements are significant for improving efficiency and robustness in applications ranging from warehouse automation and search-and-rescue to collaborative assembly and environmental monitoring.