Multi-constraint UAV Fast Path Planning Based on Improved A* Algorithm
Xiaodi Kong, Bin Pan, Evgeny Alexandrovich Cherkashin, Xiaoyang Zhang, Linke Liu, Jian Hou · Journal of Physics Conference Series · 2020
Abstract Path planning is an important part of UAV intelligent control technology. For the current UAV path planning, the A* algorithm has a large memory overhead during the planning process, and the search speed is slow. It cannot meet the path planning in a complex three-dimensional environment. The immediacy requirement and considering the constraints are less, this paper made the following improvements to the A* algorithm. The first, combining an anytime repair search framework with a weighted A* algorithm, it is possible to quickly find a feasible path during the search process. The second, aiming at the defect of relying on low heuristic function weights in the algorithm, a double ranking criterion is proposed to improve the efficiency of the algorithm approaching the optimal path in the iterative process. And third, to reduce the number of node expansions in the planning process, increase list storage constraints have been improved. Finally, the results of simulation experiments show that the improved algorithm proposed in this paper can quickly generate feasible paths, and can continuously optimize the approach to the optimal path within a specified time, which is far superior to the traditional A* algorithm in terms of planning efficiency and immediacy.