A fast path planning approach for unmanned aerial vehicles

In unmanned aerial vehicles navigation, path planning is aimed at obtaining the optimal safety path between start and destination locations. The efficiency and optimality criterion depend on the environment and planning method adopted. In this paper, a general fast path planning framework is proposed for unmanned aerial vehicles navigation. Standard A* search is performed online on the roadmap, which consists of path segments that are pre-computed offline with the aid of a multi-resolution grid and terminate at somewhere along the boundary between adjacent cells. Fast marching method (FMM) was employed for two aspects of the roadmap pre-computation: the location of segment termination points is determined by FMM propagation from the center of a given cell at the highest resolution grid, and the actual segments are computed using FMM between all pairs of nodes belonging to a given cell at all resolutions. Environment dynamics are taken into account by replanning from scratch after modifying the costs associated with the path segments that intersect threat' or no-fly' zones. The altitude along the planned path is determined in a post-processing step by inspecting the elevation profile along the path and using Sparse A*searching method. The experimental results show that planning speed can be improved significantly with the proposed method, especially, fast online path planning can be achieved to adapt to environmental changes. Copyright (c) 2014 John Wiley & Sons, Ltd.