摘要
为更好地完成大面积区域的全覆盖扫描,提出一种多车多无人机协同区域搜索模式。构建考虑卡车行驶路程限制与无人机总量限制的多车多无人机协同区域搜索模型,设计一种融合退火机制、禁忌策略与自适应大邻域搜索的三阶段优化算法(a three stage optimization algorithm integrating annealing mechanism,tabu strategy,and adaptive large neighborhood search,ALNSAWPT),通过区域划分、车辆路径规划、无人机路径规划来求解该问题。在第一阶段,设计基于网格的区域划分方法将大面积区域划分为多个搜索任务。在第二阶段,将搜索任务分配给卡车并生成卡车的路径规划方案。由此,原问题简化为多组单车多无人机协同区域搜索问题。在第三阶段,为每个卡车上的无人机分派搜索任务并生成搜索路径规划方案。实验结果表明,ALNSAWPT明显优于其他5种对比算法,且多车多无人机协同区域搜索模式的效率明显优于单车多无人机区域搜索模式,证明了所提算法的有效性。
To better achieve full coverage scanning of large-area,a multi-truck and multi-drone collaborative area search mode is proposed.A multi-truck and multi-drone collaborative area search model is constructed considering the distance limit of truck travel and the total number limit of drones.A three-stage optimization algorithm integrating annealing mechanism,tabu strategy,and adaptive large neighborhood search(ALNSAWPT)is designed to solve the problem through area partitioning,truck path planning,and drone path planning.In the first stage,a grid based area partitioning method is designed to divide a large-area into multiple search tasks.In the second stage,the search task is assigned to the truck and a path planning scheme for the truck is generated.Thus,the original problem is simplified as a collaborative area search problem involving multiple groups of multi-truck and multi-drone.In the third stage,search tasks are assigned to each drone on the truck and generate a search path planning scheme.The experimental results show that ALNSAWPT is significantly better than the other four compared algorithms,and the efficiency of the multi-truck and multi-drone collaborative area search mode is significantly better than that of the single-truck and multi-drone area search mode,proving the effectiveness of the proposed algorithm.
作者
洪芳宇
叶青
张利宁
伍国华
HONG Fangyu;YE Qing;ZHANG Lining;WU Guohua(School of Traffic and Transportation Engineering,Central South University,Changsha 410075,China;BYD Auto Industry Company Limited,Shenzhen 518118,China;Unit 93128 of the PLA,Beijing 100085,China;School of Automation,Central South University,Changsha 410017,China)
出处
《系统工程与电子技术》
北大核心
2026年第1期144-156,共13页
Systems Engineering and Electronics
基金
国家自然科学基金(62373380)资助课题。
关键词
大面积区域搜索
多卡车多无人机协同
三阶段优化算法
任务规划方法
large-scale area search
collaborative multi-truck and multi-drone
three stage optimization algorithm
task-planning method
