耦合改进JPS与DWA的无人机航迹规划

Integration of Improved JPS and DWA for UAV Trajectory Planning

针对无人机传统的航迹规划方法存在求解效率低、适用范围窄的问题,提出一种考虑全局和局部规划相耦合的航迹规划方法。首先,提出几何航迹碰撞检测法以改进跳点搜索(JPS)算法,提升无人机在全局环境中航迹规划能力;其次,提出一种耦合策略的航迹规划框架,通过将无人机全局航迹信息与动态窗口局部航迹信息进行耦合,扩展动态窗口法的评价子函数,确保无人机在动态环境中具备灵活的避障能力;最后,通过仿真实验论证了所提改进JPS算法在全局搜索时间、航迹距离和航迹转折点数目等方面较现有方法的优势,验证了耦合算法在动态环境中的稳定避障能力。

To address the problems of low calculation efficiency and limited applicability of the traditional UAV trajectory planning methods,a trajectory planning method that considers the integration of global and local planning is proposed.Firstly,a geometric track collision detection method is proposed to improve the Jump Point Search(JPS)algorithm to enhance the UAV trajectory planning capability in the global environment.Secondly,a trajectory planning framework for the integration strategy is proposed to extend the evaluation sub-function of the dynamic window method by integrating the UAV's global trajectory information with local trajectory information of the dynamic window to ensure the UAV's flexible obstacle avoidance capability in dynamic environments.Finally,the advantages of the improved JPS algorithm over existing methods in terms of global search time,trajectory distance and number of trajectory turning points are demonstrated through simulation experiments,and the stable obstacle avoidance capability of the integration algorithm in dynamic environments is verified.