首页 /研究 /A Navigation Framework Fused with 3D and 2D SLAM Algorithms for solid-state LiDARs
PERCEPTION

A Navigation Framework Fused with 3D and 2D SLAM Algorithms for solid-state LiDARs

Zhifeng Huang, Kang Ding, Zeming Liu, Kairong Wu, Yun Zhang

发表年份
2023
引用次数
2

摘要

Nowadays, most navigation frameworks for mobile robots are designed based on mechanical LiDARs, and there are relatively few navigation frameworks for solid-state LiDARs with small FoV(Field of view) which have been widely used in recent years because of its lower cost and long-range. In this paper, we present a navigation framework for solid-state LiDARs with small FoV like Livox. This framework is based on the ROS system and combines 3D SLAM algorithm Loam_Livox with 2D SLAM algorithm Gmapping. The odometer information output by Loam_Livox is used as input for the occupancy grid map construction of algorithm Gmapping. The occupancy grid map information output by algorithm Gmapping is also passed into the move_base framework to control the mobile robot for the navigation function. In the move_base framework, we use improved A-STAR and improved DWA algorithms, which can improve the working safety and efficiency of the mobile robot. As a result, this system is able to build 3D dense point cloud map and occupancy grid map in real time, which can also perform navigation tasks for the mobile robot.

关键词

Occupancy grid mappingMobile robotComputer scienceGrid referencePoint cloudMobile robot navigationGridSimultaneous localization and mappingArtificial intelligenceRobot

相关论文

查看 PERCEPTION 分类全部论文