摘要
针对传统A^(*)算法所规划路径存在易触碰障碍物,冗余节点过多等问题。提出了一种改进8邻域节点搜素策略A^(*)算法的路径规划。首先,在A算法中改进节点搜索条件,使得获得的节点与周围障碍物节点保持一定安全距离;然后利用垂距限值法剔除改进后路径上的冗余节点,并保留关键节点;最后,基于关键节点利用B样条曲线拟合出一条平滑路径。在不同规模的多障碍物地图环境下进行多次实验与对比,结果表明,相比于传统A^(*)算法,提出的改进A^(*)算法,获得的路径节点与障碍物节点的安全距离平均保持在0.46,路径节点平均减少了66.8%,有效提升机器人的工作效率和安全性。
Traditional Aalgorithms plan paths that run the risk of hitting obstacles and create too many redundant nodes.For these problems,a path planning with improved search 8-neighborhood node strategy A^(*)algorithm is proposed.Firstly,the node search condition is improved in the A^(*)algorithm so that the obtained nodes maintain a safe distance from the surrounding obstacle nodes.Secondly,the redundant nodes on the improved path are removed using the vertical distance limit method,and the critical nodes are retained.Finally,a smooth path is obtained by fitting a B spline curve to the key nodes to achieve a smooth path.By conducting several experiments and comparisons in multiple obstacle map environments of different scales.The results show that the proposed improved A^(*)algorithm,compared to the traditional A^(*)algorithm,maintains an average of 0.46 path nodes to obstacle nodes and reduces path nodes by an average of 66.8%,effectively improving the efficiency and safety of the robot.
作者
姜媛媛
张阳阳
Jiang Yuanyuan;Zhang Yangyang(School of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan 232001,China;Institute of Environment-Friendly Materials and Occupational Health,Anhui University of Science and Technology,Wuhu 241003,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2022年第5期234-241,共8页
Journal of Electronic Measurement and Instrumentation
基金
安徽省重点研究与开发计划(202104g01020012)
安徽理工大学环境友好材料与职业健康研究院研发专项基金(ALW2020YF18)项目资助。
关键词
A^(*)算法
冗余节点
节点搜索
垂距限值法
8邻域
A^(*)algorithm
redundant nodes
search node
perpendicular distance methods
eight areas
