A dense obstacle avoidance algorithm for UAVs based on safe flight corridor

Q3 Engineering
L. Fan, Haozhe Zhang, Zhao Xu, Mingwei Lyu, Jin-wen Hu, Chunhui Zhao, Xiaobin Liu
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引用次数: 1

Abstract

Aiming at the problem of autonomous obstacle avoidance of fixed-wing UAVs in a complex, dense and multi-obstacle environment, a path planning algorithm for fixed-wing UAVs based on a safe flight corridor is proposed. The difficulty of avoiding dense obstacles lies in the choice of obstacle circumvention and traversal: although circumvention is safer, the flight cost is greater; although the traversal cost is lower, the safety threat is higher. How to quickly solve the optimal path is the core issue. This paper firstly defines a safe flight corridor innovatively based on the maneuvering characteristics of fixed-wing UAVs and the Dubins curves. By comprehensively considering UAV flight safety and flight costs, an obstacle threat evaluation function is constructed. Secondly, in view of the computational complexity caused by the dense obstacles, an obstacle clustering algorithm based on obstacle density is proposed, and the nonlinear evaluation function in a high dynamic environment is quickly approximated by Monte Carlo sampling method. Finally, simulations verify the effectiveness of the proposed algorithm in solving dense obstacle avoidance for fixed-wing UAVs.
基于安全飞行走廊的无人机密集避障算法
针对固定翼无人机在复杂、密集、多障碍环境中的自主避障问题,提出了一种基于安全飞行走廊的固定翼无飞行器路径规划算法。避开密集障碍物的困难在于障碍物规避和穿越的选择:尽管规避更安全,但飞行成本更大;尽管遍历成本较低,但安全威胁较高。如何快速求解最优路径是核心问题。本文首先根据固定翼无人机的机动特性和Dubins曲线,创新性地定义了安全飞行走廊。通过综合考虑无人机飞行安全和飞行成本,构建了障碍物威胁评估函数。其次,针对密集障碍物带来的计算复杂性,提出了一种基于障碍物密度的障碍物聚类算法,并采用蒙特卡罗采样方法快速逼近高动态环境下的非线性评价函数。最后,仿真验证了该算法在解决固定翼无人机密集避障问题中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
西北工业大学学报
西北工业大学学报 Engineering-Engineering (all)
CiteScore
1.30
自引率
0.00%
发文量
6201
审稿时长
12 weeks
期刊介绍:
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