关键词: 航空运输, 路径规划, 改进A*算法, 物流无人机, 双向搜索策略

Abstract:

This paper solves the path planning problem of logistics unmanned aerial vehicle (UAV) in the urban area. The grid method is first used to model the environment with the performance of UAV, task nature, and urban environment. A multi-constrained logistics UAV path planning model is then constructed to minimize the range, height change, and risk. And an improved A* algorithm is designed to solve the model. The heuristic function uses the linear combination of Euclidean distance and Manhattan distance to estimate the distance reasonably. A twoway search strategy is introduced to improve the search efficiency. The B-spline method is applied to optimize the path in order to ensure a smooth flight. The research results show that the proposed model is effective to achieve multi-objective performance. Compared with the traditional A* algorithm, the improved algorithm can solve for a shorter path with less altitude change and stable flight safety in less computational time. When the weight coefficients of the three sub-targets are 0.4, 0.1, and 0.5 respectively, and the weights of the two distances are 0.15 and 0.85 respectively, the UAV path planned by this algorithm is the best.

Key words: air transportation, path planning, improved A* algorithm, logistics UAV, two-way search strategy