Leaderless Multi-Agent Formation Control with Collision Avoidance

In the absence of a virtual leader, multi-agent systems can achieve efficient and orderly movement through effective collaboration and communication protocols. This approach ensures collision avoidance between agents, guaranteeing system safety and stability. By establishing appropriate behavioral rules and coordination strategies (e.g., potential field methods or consensus algorithms), agents can cooperatively complete tasks with optimized outcomes. The implementation typically involves distributed controllers using relative position measurements and neighbor-based interaction protocols, often coded with state machines for behavior transitions. Furthermore, such formation systems demonstrate adaptability to dynamic environments, autonomously adjusting trajectories through real-time sensor data processing and decision-making modules (e.g., using reinforcement learning for path planning). Thus, without centralized leadership, multi-agent formations effectively leverage cooperative advantages through decentralized algorithms like gradient-based navigation or distributed optimization, achieving predefined objectives while maintaining formation geometry and safety margins through continuous inter-agent distance monitoring.