A novel path planning algorithm for virtual disassembly of components within aircraft fuel tanks
Yubin Wang, Chongyang Xu, Hualong Xie, Jianyu Yang, Zhongqi Sheng · Engineering Optimization · 2025
With the growing complexity of aircraft maintenance, virtual maintenance systems are increasingly adopted for planning and simulation. To improve the efficiency and quality of path planning in fuel tank scenarios, an Initialization Rapidly-exploring Random Tree (IRRT) algorithm is proposed to generate a benchmark path in the early planning phase, enhancing both speed and accuracy. Building on this, a Sampling Heuristic Initialization-based Particle Swarm (SHI-PSO) optimal path planning algorithm is developed for constrained workspaces, optimizing directional changes and ensuring global path quality. Experiments on a virtual maintenance system based on an actual aircraft fuel tank model show that, compared to the RRT algorithm, the proposed method reduces path length by 46.0% and direction changes by 95.1%, with similar planning time. Compared to PSO, it shortens path length by 5.7%, reduces direction changes by 84.6% and lowers planning time by 81.1%, effectively addressing the trade-off between speed and quality in path planning.