A Swarm-Based Flocking Control Algorithm for Exploration and Coverage of Unknown Environments

Abstract

The exploration of unknown environments can be beneficial for a variety of applications, such as inspection of industrial equipment, environmental monitoring, or search and rescue missions. In order to tackle this problem, swarm robotics has emerged as a promising approach due to its ability to leverage the collective behavior of a group of robots to explore an area efficiently. This paper proposes a swarmbased control algorithm for exploration and coverage of unknown environments. The algorithm utilizes shortrange distributed communication and sensing among agents, with no central unit, to coordinate the swarm’s navigation and search tasks. This sensing is prioritized in the outermost agents of the swarm to reduce processing and energy costs, and these positions can be rotated with other agents in the swarm. The formation rules that keep the system cohesive are simple and independent of the individual robot characteristics, enabling the use of heterogeneous agents. The performance of the proposed strategy is demonstrated through experiments in coverage and search tasks, and compared with other swarm strategies. The results show the effectiveness of the proposed algorithm for exploration and coverage of unknown environments. The research presented in this paper has the potential to contribute to the development of more efficient and effective swarmbased exploration and coverage strategies.