Anonymous Flocking With Obstacle Avoidance via the Position of Obstacle Boundary Point

• Published in: IEEE internet of things journal p. 1
• Main Authors: Wu, Jianhui, Ji, Yuanfa, Sun, Xiyan, Fu, Wentao, Zhao, Songke
• Format: Journal Article
• Language: English
• Published: IEEE 20.09.2024
• Subjects: Anonymous flocking; Collaboration; Collision avoidance; expected velocity; Internet of Things; multi-agents; Navigation; obstacle avoidance; obstacle boundary point; Sensors; Shape; Vectors
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2024.3465881

The collaborative control algorithms of multi-agents system have been applied to many Internet of Things (IoT) devices. The anonymous flocking algorithm of multi-agents is a core technology in the collaborative control research of multi-agents system. It does not need agents to distinguish other agents and obstacles, but most existing researches have specific constraints on the obstacle shape, which limits its practical applications. The obstacle boundary points contain the shape characteristics of the obstacle. To relax the obstacle shape constraint, we assume that all agents can only perceive the position of obstacle boundary points within their sensing radius, and propose an anonymous flocking algorithm with obstacle avoidance via the position of obstacle boundary point. In this algorithm, the consensus term is divided into velocity consensus term and velocity unit direction consensus term. The velocity consensus term is designed to tow agents that perceive the obstacle boundary points preventing them from following to bypass obstacles, and the velocity unit direction consensus term is designed to achieve the matching of velocity unit direction. Additionally, the gradient-based term is designed to realize the separation and aggregation between agents and obstacle boundary points, and the navigational feedback term is designed to lead all agents to realize the group objective following. Furthermore, it is verified through simulations that the proposed algorithm can relax obstacle shape constraint and has better environmental adaptability.