一种面向突发威胁的多因素Dubins航迹规划算法
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作者单位:

1.南京航空航天大学电子信息工程学院,南京 211106;2.北京航天自动控制研究所,北京 100854

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基金项目:

国家自然科学基金(61572254,61902182)资助项目;江苏省自然科学基金(BK20190409)资助项目;中国电子科技集团公司航天信息应用技术重点实验室开放基金(SXX18629T022)资助项目;南京航空航天大学研究生开放基金(kfjj20190413)资助项目。


Multi-factor Dubins Path Planning Algorithm for Emergent Threats
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1.College of Electronic and Information Engineering, Nanjing University of Aeronautics & Astronautics,Nanjing 211106, China;2.Beijing Aerospace Automatic Control Institute, Beijing 100854, China

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    摘要:

    针对传统无人机航迹规划算法应用在突发威胁场景下存在搜索点冗余、路径规划实时性较差等问题,提出了一种基于多因素Dubins路径的无人机动态航迹规划算法。该算法首先根据无人机自身性能约束及突发威胁区域的位置,并且考虑无人机的起始和最终位置,利用传统的Dubins路径找到有效的路径扩展点。然后结合启发式搜索思想建立基于路径长度和威胁的路径扩展点评估函数。最后通过路径评估函数计算,比较路径点的代价值,选取每一步的路径扩展点,规划出较优路径。仿真结果表明,在突发威胁场景下利用该算法进行航迹规划时路径长度较短、路径扩展点较少,并且符合无人机实际飞行过程中航向角变化,可有效保障无人机的安全性和航迹规划的实时性。

    Abstract:

    As traditional UAV trajectory planning algorithms generate redundant search points and poor real-time path planning in emergent threat scenarios, a dynamic trajectory planning algorithm for UAVs based on multi-factor Dubins path is proposed. First, the algorithm uses the traditional Dubins path to find effective path extension points based on the UAV’s own performance constraints and the location of the sudden threat area. Sencond, a path extension point evaluation function is established based on the path length and threat combined with heuristic search ideas. Finally, the path extension point is selected through the path evaluation function, and a better path is planned. The simulation results show that when the algorithm is used for trajectory planning in sudden threat scenarios, the path length is shorter and the path extension points are fewer, and it conforms to the change of the heading angle of the drone during the actual flight, which can effectively ensure the safety of the drone and real-time trajectory planning.

    图1 Dubins最短路径Fig.1 The shortest path of Dubins
    图2 扩展点选择Fig.2 Extension point selection
    图3 人工势场法基本原理Fig.3 Basic principles of artificial potential field method
    图4 MFDA算法路径规划过程Fig.4 Path planning process of MFDA
    图5 LSR路径类型Fig.5 Path type of LSR
    图6 单威胁区域场景下航迹规划结果Fig.6 Track planning results under single threat area scenario
    图7 双威胁区域场景下航迹规划结果Fig.7 Track planning results under two threat zone scenarios
    图8 多个威胁区域场景下航迹规划结果Fig.8 Track planning results under multiple threat area scenarios
    图9 3个场景下路径规划长度Fig.9 Path planning length under three scenarios
    图10 3个场景下路径扩展点数量Fig.10 Number of path extension points under three scenarios
    图11 3个场景下路径规划时间Fig.11 Path planning time under three scenarios
    图12 路径航向变化Fig.12 Change of course heading
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黄加红,白丽,范兼睿,张莉涓,雷磊.一种面向突发威胁的多因素Dubins航迹规划算法[J].数据采集与处理,2021,36(6):1137-1146

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  • 收稿日期:2020-09-10
  • 最后修改日期:2021-02-20
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  • 在线发布日期: 2021-11-25