VIO-wheel-stereo mapping: an indoor room structure mapping system using monocular camera, IMU, wheel odometry and stereo

Xin Li, Kaibin Chu, Ji Zhang, Tingting Hao
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Abstract

This paper proposes an indoor house structure mapping system, which mainly studies the SLAM positioning, laser depth binocular camera locally built figure, robot path planning, and other issues. And the three-dimensional indoor autonomous robot is built based on called VINS system. With wheel odometry and sensor fusion, this paper realizes the robot chassis indoor high-precision positioning, indoor autonomous robots scanning walls. Finally, through the integration of several modules, the chassis robot can achieve the function of indoor independent three-dimensional drawing. This system is successfully applied on a 4-wheel mecanum small car. I take a 20 square meters underground parking lot in as the experiment area. The test shows that the system of displacement drift error within 2% and the ratio of the overall path, room-built figure area error within 3%, loopback positioning error is less than 0.1 m, the robot can work independently to complete the building figure. In the end, the system is evaluated and a commercial indoor 3D drawing scheme is proposed.
VIO-wheel-stereo mapping:一种利用单目相机、IMU、wheel odometry和stereo的室内房间结构测绘系统
本文提出了一种室内房屋结构测绘系统,主要研究SLAM定位、激光深度双目相机局部构建图、机器人路径规划等问题。并基于VINS系统构建了三维室内自主机器人。采用车轮里程计和传感器融合技术,实现了机器人底盘室内高精度定位,室内自主机器人扫描墙面。最后,通过几个模块的集成,底盘机器人可以实现室内独立三维绘图的功能。该系统已成功应用于一辆四轮机械小车上。我选择了一个20平米的地下停车场作为实验区。测试表明,该系统的位移漂移误差与整体路径的比值在2%以内,室内建图面积误差在3%以内,环回定位误差小于0.1 m,机器人可以独立工作完成建图。最后,对系统进行了评估,并提出了一个商业化的室内三维绘图方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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