Multi-agent flocking with obstacle avoidance and safety distance preservation: a fuzzy potential-based approach

In this paper, a control method is proposed for the flocking of multi-agent systems in the presence of obstacles. One of the main contributions of this work is the introduction of a safety distance parameter that ensures agents do not enter this safety distance during the flocking process. To achieve this, a fuzzy logic-based gradient of the potential function is designed. Furthermore, it is demonstrated that no consensus term is necessary in the control signal when all agents are informed about the desired path. Additionally, stability analysis is conducted for the proposed algorithm in free space, which allows the extraction of the ultimate bound of the tracking error. Finally, the effectiveness of the proposed algorithm is demonstrated through simulations conducted in free space, space with obstacles, and in the presence of measurement noise. The results obtained from these simulations are compared with the existing methods in the literature.