电子学报 ›› 2017, Vol. 45 ›› Issue (7): 1764-1769.DOI: 10.3969/j.issn.0372-2112.2017.07.029

• 学术论文 • 上一篇    下一篇

基于改进RRT算法的无人机航迹规划

尹高扬, 周绍磊, 吴青坡   

  1. 海军航空工程学院控制科学与工程系, 山东烟台 264001
  • 收稿日期:2015-12-25 修回日期:2016-10-08 出版日期:2017-07-25
    • 作者简介:
    • 尹高扬,男,1987年6月出生于湖南湘潭,从事导航、制导与控制相关研究.E-mail:ygy3632@163.com;Tel:15969659253;周绍磊,男,1963年1月出生于山东淄博,教授、博士生导师,主要研究领域为控制与测试.
    • 基金资助:
    • 航空科学基金 (No.20135184007)

An Improved RRT Algorithm for UAV Path Planning

YIN Gao-yang, ZHOU Shao-lei, WU Qing-po   

  1. Department of Control Engineering, Naval Aeronautical and Astronautical University, Yantai, Shandong 264001, China
  • Received:2015-12-25 Revised:2016-10-08 Online:2017-07-25 Published:2017-07-25

摘要:

针对快速扩展随机树(RRT)算法用于无人机自主在线航迹规划时,只能快速获得可行的航迹,无法获得接近于最短航迹的较优航迹的缺点,提出了一种改进的RRT算法.该算法将无人机动力学约束融入到节点扩展过程中,通过改进离随机采样点最近的根节点的选取策略和引入航迹距离约束,搜索树将沿着航迹距离较短的方向朝着目标点进行扩展,使得规划出来的航迹接近最优,并采用基于B样条曲线的航迹平滑方法生成平滑可跟踪的航迹.仿真结果表明该算法能够快速地搜索安全并且满足无人机动力学约束的较优航迹.

关键词: 无人机, 快速扩展随机树, 实时性, 航迹距离约束, 航迹平滑

Abstract:

To solve the problem that the basic RRT algorithm for UAV path planning can only quickly get feasible path,unable to obtain near optimal path,an improved RRT algorithm is proposed.The algorithm takes into account the dynamic constraints of UAV,by introducing the path length constraint and improving the selection strategy for root node that nearest to the random sample point,the search tree will explore along the direction of the near optimal path.Flyable path is generated by using B-spline curves for path smoothing.Simulation results demonstrated that this proposed method can complete UAV path planning mission quickly and effectively.

Key words: unmanned aerial vehicle(UAV), rapidly-exploring random tree, real-time, path length constraint, path smoothing

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