融合A^(*)和TEB算法的巡检机器人路径规划研究  

Research on Path Planning of Inspection Robots Integrating A^(*)and TEB Algorithms

作　　者：穆莉莉[1] 王超[1] 史程 王天棋 Mu Lili;Wang Chao;Shi Cheng;Wang Tianqi(School of Mechanical and Electrical Engineering,Anhui University of Science and Technology,Huainan,Anhui 232001,China)

机构地区：[1]安徽理工大学机电工程学院,安徽淮南232001

出　　处：《黑龙江工业学院学报（综合版）》2024年第3期143-149,共7页Journal of Heilongjiang University of Technology(Comprehensive Edition)

基　　金：安徽省重点研发项目(项目编号:202004a07020046)。

摘　　要：针对激光雷达智能巡检机器人在复杂环境下静态障碍物路径规划复杂,动态障碍物躲避效果不佳等问题,提出一种路径规划融合算法以提高机器人避障效果。采用Karto-SLAM进行激光SLAM建图,将A^(*)算法与TEB算法有效融合完成机器人的全局路径规划与局部路径规划。仿真实验与实测表明,通过Karto算法所建地图的平均误差约为1.259%,A^(*)与TEB的融合算法在完成单一A^(*)算法最优路径生成的同时还具备良好的避障功能,有效避障率达到90%以上,满足巡检机器人移动避障等要求。Aiming at the problems that the laser radar intelligent inspection robot has a complex path planning for static obstacles and poor avoidance effect of dynamic obstacles in a complex environment,this paper proposes a path planning fusion algorithm to improve the robot′s obstacle avoidance effect.First,Karto-SLAM is used for laser SLAM mapping,and then the A^(*)algorithm and the TEB algorithm are effectively fused to complete the global path planning and local path planning of the robot.Simulation experiments and actual measurements show that the average error of the map built by the Karto algorithm is about 1.259%.The fusion algorithm of A^(*)and TEB not only completes the optimal path generation of the single A^(*)algorithm,but also has a good obstacle avoidance function,effectively avoiding obstacles.The rate reaches more than 90%,which meets the mobile obstacle avoidance requirements of inspection robots.

关 键 词：激光雷达 巡检机器人 路径规划 动态避障 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]