摘要
Abstract
To address the problems of low localization accuracy and poor navigation efficiency of mobile robots in complex indoor environments,this paper designed an autonomous localization and navigation system based on the Robot Operating System(ROS),aiming to improve the robot's autonomy and adaptability in unknown or dynamic environments.The system used an Nvidia Jetson Nano 4GB as the computing platform and fused laser radar,wheel odometry,and an inertial measurement unit.Real-time pose estimation was achieved through the Adaptive Monte Carlo Localization(AMCL)algorithm.The Dijkstra algorithm was employed to plan the global optimal path,and motion control together with dynamic obstacle avoidance was realized via serial communication between the upper and lower computers and coordination of ROS nodes.In laboratory scenarios,the system was able to build a costmap in real time and generate the shortest collisionfree path from the start point to the target point.During operation,the robot effectively avoided obstacles,and both the localization and navigation functions were experimentally validated.The proposed system achieved autonomous localization and navigation for indoor mobile robots,exhibiting good stability and realtime performance,and met the application requirements in complex environments.关键词
移动机器人/室内环境/自主移动/路径规划/激光SLAM/Dijkstra算法Key words
mobile robot/indoor environment/autonomous movement/path planning/Lidar SLAM/Dijkstra algorithm分类
信息技术与安全科学
