Communication and Control in Multi-Agent Robotic Systems

Multi-agent robotic systems (MARS) have emerged as a pivotal paradigm in robotics, enabling complex tasks through the collaboration of multiple autonomous agents. Effective communication and control mechanisms are essential for the coordination and efficiency of these systems. This paper delves into the current advancements in communication protocols and control strategies within MARS, highlighting the integration of machine learning techniques to enhance system performance. Through a comprehensive analysis of recent studies, we identify key challenges and propose potential solutions to optimize communication and control in multi-agent robotic systems.