A Three-Dimensional Path Planning Method for Unmanned Aerial Vehicles Based on Improved Dung Beetle Optimization Algorithm
Liqing Su, Yuanli Cai · 2023
A heuristic algorithm based unmanned aerial vehicle (UAV) for path planning in mountainous areas has slow convergence speed, poor path planning quality, and is prone to falling into local optima. The present study proposes an enhanced UAV 3D path planning approach based on the dung beetle optimization algorithm to tackle this issue. The improvement method is as follows: introducing a reverse learning strategy involving lens-based imaging into the conventional dung beetle optimization algorithm to expand exploration within the search space, thereby balancing local optimization and global optimization capabilities; During the reproduction stage of dung beetles, a dynamic helical exploration approach is implemented to broaden the search span and enhance the speed of convergence; During the foraging stage of dung beetles, an optimal value guidance strategy is introduced to guide the generation of candidate solutions. Compared with traditional dung beetle optimization algorithms, The findings indicate that the improved method proposed in this paperexhibits enhanced rate of convergence and is not easily trapped in local optima. The simulation experiment of mountain path planning shows that this method improves the quality of path planning by 11.52% compared to traditional algorithms.