Distributed Swarm Robot Control Using Fuzzy Logic, Chaos Theory, and the Dragonfly Algorithm

Abstract

When swarm robots move in an environment with obstacles to search for an unknown target, the challenge is that each individual robot must be able to maintain swarm cohesion, avoid obstacles, and achieve the widest possible coverage of the search space. Therefore, this paper proposes a solution that applies fuzzy logic to determine the steering angle of robots in the swarm, which helps adjust collision avoidance behaviors and regulate robot distribution within the environment. At the same time, the paper integrates chaos theory and the Dragonfly Algorithm (DA) to improve the quality of swarm control, enabling the robots to move more flexibly, avoid obstacles smoothly, and achieve the best possible coverage of the target search space during the entire process.