Path Planning and Control for Multiagent Traversing Numerous Obstacles

To ensure that multiagent’s collision-free traversal in a complex 3-D space with numerous obstacles, this article proposes an online centralized path planning and distributed tracking control method. First, considering the position and overall size of the numerous obstacles in 3-D space, a threat model is established by using Gaussian mixture model, which assigns a different threat level to each location in the 3-D space, with closer obstacles posing a greater threat. Subsequently, five rules are defined based on the threat model, namely, target steering, minimal threat, threat threshold, direct connection, and mixed threat. A combination of these rules is used to design a shortest, collision-free, and fast path planning algorithm for the multiagent. To ensure holistic optimality, multiagent path planning is designed as a centralized computation. A distributed tracking control algorithm is then designed based on model predictive control. Finally, the proposed methods are verified by both numerical simulations and semiphysical simulations based on the air-float experimental system, proving the stable generation of collision-free traversal paths in numerous obstacles, and the accurate tracking control. The simulations show that the proposed methods have the characteristics of minimal path length, high-efficiency computation, robust security, general applicability, and small control error.