摘要
针对传统A*算法存在拐点冗余、搜索效率低和规划路径曲折等问题,提出一种改进A*算法与改进动态窗口法相结合的融合算法,用于移动机器人的路径规划。针对拐点冗余问题,通过提取关键节点有效去除无用拐点;针对搜索效率低问题,在评价函数的启发函数中引入动态加权因子,改变搜索邻域,减少搜索节点,提高算法运行效率;针对规划路径曲折问题,对规划后的路径使用改进动态窗口法进行优化,提高路径平滑度。通过MATLAB仿真对比实验,证明融合算法在全局路径优化方面的优势,有效减少路径冗余节点数量、缩短路径长度。此外,所提融合算法能够增加机器人路径平滑度和运动稳定性。
The traditional A*algorithm is computationally simple and has short planning paths,but it still suffers from redundancy of inflection points,low search efficiency and zigzagging planning paths.Aiming at the above problems,a fusion algorithm combining the improved A*algorithm and the improved dynamic window approach is proposed for the path planning of mobile robots.For the problem of redundant inflection points,the key nodes are extracted to effectively remove the useless inflection points;for the problem of low search efficiency,a dynamic weighting factor is introduced into the heuristic function of the evaluation function,which changes the search neighborhood and reduces the search nodes to improve the operation efficiency of the algorithm;for the problem of zigzagging of the planning paths,the paths are optimized using the improved dynamic window approach,which improves the smoothness of the paths.Through Matlab simulation and comparison experiments,the fusion algorithm is proved to be advantageous in global path optimization,effectively reducing the number of redundant nodes in the path and shortening the path length.In addition,the proposed fusion algorithm can increase the robot path smoothness and motion stability.
作者
赖荣燊
窦磊
巫志勇
孙帅
Lai Rongshen;Dou Lei;Wu Zhiyong;Sun Shuai(Mechanical and Automotive Engineering,Xiamen University of Technology,Xiamen 361024,China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2024年第8期1884-1894,共11页
Journal of System Simulation
基金
福建省自然科学基金(2022J011246)
科技部创新方法工作专项(2019IM010300)。
关键词
A*算法
动态窗口法
融合算法
路径规划
路径平滑
A*algorithm
dynamic window approach
fusion algorithm
path planning
path smoothing
