基于改进人工势场方法的无人机群侦察覆盖航路规划算法研究

Research on the Route Planning Algorithm of UAV Group Reconnaissance Coverage Based on Improved Artificial Potential Field Method

摘要: 随着无人机平台技术的逐渐成熟和广泛应用，利用无人机平台执行侦察任务的效费比也越来越高。无人机群的航路规划是侦察任务规划中的核心问题。面对复杂的侦察任务，基于解析的方法适应性不强、自动化程度较低。因此，本文提出了一种基于人工势场的无人机群侦察航路规划方法。在无人机责任区域划分的研究中，针对规则区域仍然采用基于解析的方法，针对不规则区域的划分，设计了基于人工势场的区域划分方法，提高了算法的适应性和自动化程度。在无人机航路生成算法中，利用种子的概念提高了无人机航路生成模式的多样性。最后通过计算实验，验证了方法的高效性和适应性。

Abstract: With the maturity and wide application of UAV platform technology, the effective cost ratio of using UAV platform to perform reconnaissance missions is also increasing. The route planning of UAV group is the core problem in reconnaissance mission planning. In the face of complex reconnaissance tasks, the analytical-based method is less adaptable and less automated. Therefore, this paper proposes a method of UAV group reconnaissance route planning based on artificial potential field. In the study of UAV responsibility region division, for the regular regions, the analytical-based method is still adopted; for the division of irregular regions, an artificial potential field region division based on artificial potential field is designed to improve the adaptability and automation of the algorithm. In UAV route generation algorithm, the concept of seed is used to improve the diversity of UAV route generation modes. Finally, the high efficiency and adaptability of the method are verified by computational experiments.