基于改进RRTStar算法的无人驾驶车辆全局路径优化研究

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关键词：车辆；无人驾驶；RRTStar算法；路径规划中图分类号：TP392 文献标志码：A 文章编号：1671-5276（2025）05-0234-06

Research on Global Path Optimization of Unmanned Vehicles Based on Improved RRT Star Algorithm

DENG Shengyin （Lanzhou Modern VocationalCollege，Lanzhou 73o2o7，China）

Abstract：Animproved pathoptimization method for theRRT Staralgorithm is designed addressing the issues of poor smoothness andobstacleavoidance performance in traditionalRRTalgorithms.Basedonthe limitationsof traditional RRT algorithms，an angle constrained sampling strategy is added to limit the maximum turning angle of the path. The collisiondetection strategy using envelope circles isused toenhance path securityand generate initial paths.With the gradientdescentalgorithm，secondaryoptimizationontheinitialpathisperformed，andthefinalpathforthevehicleto travel is abtained.The results show that compared to traditional RRT Star path planning，the improvedRRT Star algorithm has significant advantages in average curvature，average rotation angle，and minimum distance，with fewer obstacle avoidance nodes and smoother curves，which verifies the feasibilityof improvement on RRT Star algorithm for path planning.

Keywords：vehicles;autonomous driving；RRT Star algorithm；path plannint

0 引言

实现移动机器人全局路径显著优化。（剩余6536字）