UAV 3-D Path Planning Based on Particle Swarm Optimization Algorithm in Complex Terrain
Mengjie Yang, Pengjun Mao · 2024
To solve UAVs’ problems of inefficient search, redundant paths, and local optimal solutions in complex terrain, this study proposes an improved method based on the particle swarm optimization (PSO) algorithm. First, it built a complex terrain environment model with multiple obstacles and introduced a Tent chaotic mapping function to initialize the particle swarm in the standard PSO algorithm to enhance the global search capability. Secondly, it included the Lévy flight to widen the search in space and help the particles overcome the local optimum. At the same time, it adopted the variable spiral search strategy to enable a precise search at its current position when the local optimum occurs. Finally, it used the B spline curve to smooth the optimized path. The results show that the improved algorithm generates a reliable path that meets the needs of UAVs.