计算机工程与应用2025，Vol.61Issue(20)：114-122,9.DOI:10.3778/j.issn.1002-8331.2407-0198
概率采样和目标偏置的变步长RRT*机器人路径规划
Probabilistic Sampling and Target-Biased Variable Step-Length RRT*for Robot Path Planning
摘要
Abstract
To address the issues of high randomness,low efficiency,long search time,and poor path quality in traditional RRT*algorithm for path planning,a new efficient method named ASP-RRT*is proposed.This method combines task require-ments and environmental characteristics to construct a comprehensive evaluation function that includes target distance,reference path distance,and obstacle complexity.The map environment is divided into different areas,and this evaluation function is used to score each area and calculate its sampling probability.Based on this probability,two types of random sampling points are designed:the first type is used to guide the overall direction of path exploration,and the second type is used to optimize the local path.At the same time,a target bias strategy is used to further control the selection of the sec-ond type of sampling points,accelerating the expansion speed towards the target.Additionally,a dynamic step strategy is adopted to adjust the expansion distance of RRT* dynamically according to the complexity of obstacles.Finally,cubic spline interpolation is applied in segments to optimize the path,making it more suitable for robot movement.Simulation experiments are conducted in six different environments,and the results demonstrate that ASP-RRT*outperforms existing sampling-based path planning methods in terms of time efficiency and path quality,and it exhibits high feasibility.关键词
路径规划/评价函数/RRT*/ASP-RRT*/目标偏置/三次样条插值法Key words
path planning/evaluation function/RRT*/ASP-RRT*/target bias/cubic spline interpolation分类
信息技术与安全科学引用本文复制引用
盛兆康,宋家乐,水翔,宋廷强,孙媛媛..概率采样和目标偏置的变步长RRT*机器人路径规划[J].计算机工程与应用,2025,61(20):114-122,9.基金项目
山东省自然科学基金青年项目(ZR2021QC120) （ZR2021QC120）
国家自然科学基金青年项目(32301702). （32301702）
