车辆支持的多无人机多区域覆盖路径规划算法
2024,46(6):227-234
田双喜
湖南财政经济学院 工商管理学院, 湖南 长沙 410205;
国防科技大学 系统工程学院, 湖南 长沙 410073，tsx_0726@nudt.edu.cn,binjie_xu@csu.edu.cn
陈洪辉
国防科技大学 系统工程学院, 湖南 长沙 410073
徐彬杰
中南大学 交通运输工程学院, 湖南 长沙 410075，tsx_0726@nudt.edu.cn,binjie_xu@csu.edu.cn
伍国华
中南大学 交通运输工程学院, 湖南 长沙 410075
湖南财政经济学院 工商管理学院, 湖南 长沙 410205;
国防科技大学 系统工程学院, 湖南 长沙 410073，tsx_0726@nudt.edu.cn,binjie_xu@csu.edu.cn
陈洪辉
国防科技大学 系统工程学院, 湖南 长沙 410073
徐彬杰
中南大学 交通运输工程学院, 湖南 长沙 410075，tsx_0726@nudt.edu.cn,binjie_xu@csu.edu.cn
伍国华
中南大学 交通运输工程学院, 湖南 长沙 410075
摘要：
针对无人机在区域侦察中的应用研究,提出车辆支持的多无人机覆盖侦察的车机协同模式与协同路径规划算法。以最小化任务完成时间为目标,考虑车辆路径所受的道路约束以及无人机的能量约束,建立混合整数规划模型,并设计基于迭代松弛思想的启发式算法。在构建的60 km2的测试场景中随机设置16个目标区域,算法实现了车辆与无人机的覆盖路径规划,全部侦察任务完成用时为1.593 h,验证了车辆支持多无人机模式的可行性以及算法的有效性。
针对无人机在区域侦察中的应用研究,提出车辆支持的多无人机覆盖侦察的车机协同模式与协同路径规划算法。以最小化任务完成时间为目标,考虑车辆路径所受的道路约束以及无人机的能量约束,建立混合整数规划模型,并设计基于迭代松弛思想的启发式算法。在构建的60 km2的测试场景中随机设置16个目标区域,算法实现了车辆与无人机的覆盖路径规划,全部侦察任务完成用时为1.593 h,验证了车辆支持多无人机模式的可行性以及算法的有效性。
基金项目：
国家自然科学基金资助项目(62073341)
国家自然科学基金资助项目(62073341)
Coverage path planning algorithm for multi-area by truck-supported multi-UAV
TIAN Shuangxi
School of Business, Hunan University of Finance and Economics, Changsha 410205, China;
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China,tsx_0726@nudt.edu.cn,binjie_xu@csu.edu.cn
CHEN Honghui
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
XU Binjie
School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China,tsx_0726@nudt.edu.cn,binjie_xu@csu.edu.cn
WU Guohua
School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China
School of Business, Hunan University of Finance and Economics, Changsha 410205, China;
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China,tsx_0726@nudt.edu.cn,binjie_xu@csu.edu.cn
CHEN Honghui
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
XU Binjie
School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China,tsx_0726@nudt.edu.cn,binjie_xu@csu.edu.cn
WU Guohua
School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China
Abstract：
To study the application of UAVs (nmanned aerial vehicles) in area reconnaissance, a cooperation mode of truck-supported multi-UAV coverage reconnaissance and a collaborative path planning algorithm were proposed. With the goal of minimizing the task completion time, a mixed integer programming model was established considering the road constraints on the vehicle path and the energy constraints of the UAVs. A heuristic algorithm based on the idea of iterative relaxation was designed. In the test scene of 60 km2,16 target areas were randomly set. The proposed algorithm realizes the coverage path planning of the truck and the UAVs, and the total reconnaissance task time is 1.593 h, which verifies the feasibility of the vehicle supporting the multi-UAV mode and the effectiveness of the algorithm.
To study the application of UAVs (nmanned aerial vehicles) in area reconnaissance, a cooperation mode of truck-supported multi-UAV coverage reconnaissance and a collaborative path planning algorithm were proposed. With the goal of minimizing the task completion time, a mixed integer programming model was established considering the road constraints on the vehicle path and the energy constraints of the UAVs. A heuristic algorithm based on the idea of iterative relaxation was designed. In the test scene of 60 km2,16 target areas were randomly set. The proposed algorithm realizes the coverage path planning of the truck and the UAVs, and the total reconnaissance task time is 1.593 h, which verifies the feasibility of the vehicle supporting the multi-UAV mode and the effectiveness of the algorithm.
收稿日期：
2022-07-26
2022-07-26
