基于定向A*算法的多无人机同时集结分步策略
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作者单位:

(1. 燕山大学工业计算机控制工程河北省重点实验室,河北秦皇岛066004;2. 燕山大学国家冷轧板带装备及工艺工程技术研究中心,河北秦皇岛066004;3. 国网黑龙江省电力有限公司佳木斯供电公司,黑龙江佳木斯154002;4. 燕山大学电气工程学院,河北秦皇岛066004)

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E-mail: xiashun9388@163.com.

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V249

基金项目:

国家自然科学基金项目(61573305).


Serial strategy for rendezvous of multiple UAVS based on directional A* algorithm
Author:
Affiliation:

(1. Key Lab of Industrial Computer Control Engineering of Hebei Province,Yanshan University,Qinhuangdao066004,China;2. National Engineering Research Center for Equipment and Technology of Cold Strip Rolling,Yanshan University,Qinhuangdao066004,China;3. Jiamusi Electric Power Company,State Grid Heilongjiang Electric Power Co., Ltd,Jiamusi154002,China;4. School of Electrical Engineering,Yanshan University,Qinhuangdao066004,China)

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    摘要:

    设计一种基于定向A*算法的多无人机同时集结分步策略.首先,提出一种定向A*算法,将无人机最大俯仰角与偏航角作为A*算法搜索约束,从而缩小节点扩展区域,并通过循环寻优规避“死区”点,进而产生平滑可飞的预规划航迹;其次,论述了补偿航程差的变步长多点搜索、三维盘旋机动、虚拟威胁等分步再规划算法,使得多无人机同时集结于目标点附近.仿真结果表明,所提出的算法能够有效完成多无人机同时集结任务.

    Abstract:

    In this paper, a serial strategy based on the directional A* algorithm for multiple UAVs is proposed. Firstly, the directional A*algorithm is presented to create a smooth and feasible pre-planning route, in which the maximum pitch and yaw angles are used as search constraints of the A* algorithm to narrow expansion area of nodes, and the successive trial and error procedure is adopted to avoid "dead zones". Then, the serial re-planning algorithm is discussed to extend the path length for aggregating at the same time, which generally consists of three steps: variable step size and multiple nodes, three-dimensional circle maneuver and virtual threats. Finally, the effectiveness of the proposed algorithm is demonstrated using numerical simulation.

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陈志旺,夏顺,李建雄,等.基于定向A*算法的多无人机同时集结分步策略[J].控制与决策,2019,34(6):1169-1177

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  • 在线发布日期: 2019-05-09
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