To address the challenges of high computational complexity, inferior path performance, and the balance between path quality and efficiency in traditional 3D omnidirectional path planning algorithms for UAVs, this study proposes an innovative precision algorithm for solving 3D omnidirectional shortest paths. The algorithm innovatively introduces the concepts of circling path and overpass path, reducing three-dimensional omnidirectional path computation to two-dimensional processing. It designs a three-view obstacle detection algorithm to achieve efficient obstacle avoidance judgment, formulates separate path-solving strategies for discrete and continuous obstacles, respectively, and obtains optimal solutions through recursive adjustments and path optimization. Experimental results demonstrate that compared to A* and Theta* algorithms, our approach achieves shorter path lengths with superior stability; the proposed algorithm achieves a 21. 86% reduction compared to RRT*, 10. 48% compared to A*, and 0. 89% compared to LazyTheta*. In addition, the proposed algorithm exhibits enhanced adaptability in high-obstacle environments (particularly irregular obstacles). These findings provide an effective solution for complex spatial path planning in UAV applications.
Zhang et al. (Thu,) studied this question.