Smooth Obstacle Avoidance Path Planning for UAVs via Hybrid Tabu-CPO Algorithm
Xiyue Chen, Tong Li, Hongying Zhang, Jiangfeng Yue, Boxian Lin, Mengji Shi, Kaiyu Qin · 2025
In this paper, a smooth obstacle avoidance path planning scheme for UAVs based on the hybrid Tabu-Crested Porcupine Optimization (Tabu-CPO) algorithm is designed. This scheme combines the Crested Porcupine Optimization (CPO) algorithm with Tabu search to enhance global search capabilities, effectively avoiding local optima through a Tabu list mechanism. At first, chaos mapping diversifies the initial population, improving search efficiency and convergence speed. Then, Bézier curves are integrated to ensure smoother and continuous paths that adhere to UAV dynamic constraints. Finally, simulation experiments validate the effectiveness of the hybrid Tabu-CPO algorithm, demonstrating its superior adaptability and optimization performance compared to traditional methods such as PSO, ACO, EEFO, and AFSA in complex environments with geometric obstacles.