Research on UAV Smooth Path Planning Method Based on Improved Ant Lion Algorithm
Hao Wang, Huajun Gong, Xinhua Wang, Huan Liang · 2021
UAV path planning is a key part of UAV's realization of intelligence. In the actual three-dimensional flight environment, it will be subject to many constraints, including the influence of terrain and obstacles and the constraints of the flight dynamics of the aircraft itself. In addition, the three-dimensional environment is more complicated than the two-dimensional environment. The traditional ALO algorithm is not satisfactory in the three-dimensional path planning, and it has defects in both the optimization efficiency and the optimization ability. In response to these problems, firstly, a dynamic convergence adaptive weight (DCAW) factor is proposed to improve the Antlion position update method, so that the explored path can maintain the optimal path; secondly, in order to reduce the amount of calculation, a chaotic search is proposed to replace the random walk of ants; finally introducing the B-spline curve smooth path design theory to smooth the optimized path can obtain a smooth and optimal path suitable for UAV flight. And the simulation results prove the feasibility and superiority of the improved algorithm.