基于KF-RRT算法的无人机动态路径规划

Hang Yan, Xingjian Fu
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引用次数: 0

摘要

针对无人机的动态路径规划问题,提出了一种基于卡尔曼滤波和改进快速探索随机树(KF-RRT)的算法。首先,在RRT算法的基础上,增加目标区域趋势权系数,减少无人机路径规划时间;其次,加入卡尔曼滤波预测函数,对动态障碍物的运动轨迹进行提前预测;然后利用b样条曲线进行平滑,规划无人机可行路径;最后,通过仿真将本文提出的KF-RRT算法与其他RRT算法进行了比较,结果表明本文提出的算法更适合无人机的动态路径规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic Path Planning of UAV Based on KF-RRT Algorithm
For the dynamic path planning of UAV, an algorithm based on Kalman Filter and improved Rapid-exploration Random Tree (KF-RRT) is proposed. Firstly, on the basis of the RRT algorithm, the weight coefficient of the target area trend is added, which reduces the time of UAV path planning. Secondly, the prediction function of Kalman Filter is added to predict the motion trajectory of dynamic obstacles in advance. Then, B-spline curve is used for smoothing to plan the feasible path of UAV. Finally, the KF-RRT algorithm in this paper is compared with other RRT algorithms by simulation, which shows that the proposed algorithm is more suitable for the dynamic path planning of UAV.
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