Intelligent Coordination for a Swarm of Autonomous Mobile Robots

Abstract

This study addresses the challenge of formation control and navigation in swarms of mobile robots, presenting an innovative algorithm that integrates behavioral approaches with fuzzy logic to calculate behavior weights for Efficient, adaptive coordination dynamically. Using a leader-follower mechanism enhanced by a virtual leader, the algorithm enables coordinated swarm movement in complex environments. The methodology combines fuzzy logic with a behavioral strategy, allowing mobile robots to adjust their actions based on environmental cues and swarm dynamics without predefned paths. Simulated experiments show the algorithm's capability to maintain formation integrity and navigate obstacles, significantly improving swarm adaptability and operational efficiency. The findings suggest a promising direction for developing intelligent mobile robotic systems capable of complex, autonomous tasks, contributing to the field of swarm robotics with a novel approach to formation control and navigation that balances individual autonomy with collective behavior.