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An Improved A* Algorithm for UAV Path Planning Problems

机译:无人机路径规划问题的一种改进的A *算法

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摘要

Recently unmanned aerial vehicle (UAV) has been widely applied in military and civil fields due to its strong autonomic and adaptability. Compared with the manned vehicles, UAV has significant advantages in carrying out the dangerous work by keeping human life away from risks. Although UAV provides notable benefits to practical applications, it gives rise to a complex path planning problem. The optimal flying path of a UAV should be obtained such that the flight length and time cost can be reduced as much as possible. In this paper, we study the path planning problem and propose an improved A* algorithm to solve the problem. First, with the models of UAVs and regions, an exact formulation based on mixed integer linear programming (MILP) is introduced to completely search the solution space. Then, by improving the evaluation function and the node selection strategy, an improved A* algorithm is presented to produce an optimal flight path for UAVs. Experimental results show that the approach proposed is more effective to solve the path planning problem than the traditional algorithms.
机译:近年来,由于其强大的自主性和适应性,无人机已广泛应用于军事和民用领域。与有人驾驶的车辆相比,无人机在使危险的人的生命远离危险的情况下具有执行危险工作的显着优势。尽管无人机为实际应用提供了显着的好处,但它引起了一个复杂的路径规划问题。应该获得无人机的最佳飞行路径,以使飞行长度和时间成本能够尽可能减少。在本文中,我们研究了路径规划问题,并提出了一种改进的A *算法来解决该问题。首先,利用无人机和区域模型,引入基于混合整数线性规划(MILP)的精确公式,以完全搜索解空间。然后,通过改进评估函数和节点选择策略,提出了一种改进的A *算法,以产生无人机的最优飞行路径。实验结果表明,所提出的方法比传统算法更有效地解决了路径规划问题。

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