Path Planning Strategy and Performance Analysis of Unmanned Aerial Vehicle (UAV) Based on Chaotic Optimization Algorithm

Currently, Unmanned Aerial Vehicle (UAV) technology has been widely applied in various industries. Based on the problem of UAV path planning in complex environments, this paper proposes a path planning strategy based on the chaotic optimization algorithm. Due to the randomness and ergodicity of the chaotic system, the path search process is optimized to avoid getting trapped in local optima. At the same time, a path planning model that includes obstacle avoidance and flight range limitations is constructed, and the chaotic optimization algorithm is combined to achieve efficient global search. Through simulation experiments, the strategy proposed in this study is compared with the traditional Particle Swarm Optimization (PSO) algorithm and A* algorithm. The results show that this strategy has certain advantages in UAV path planning and has better convergence stability, providing a new idea for UAV path planning.