激光SLAM移动机器人室内定位研究

doi:10.13474/j.cnki.11-2246.2019.0376

测绘通报 ›› 2019, Vol. 0 ›› Issue (12): 8-11.doi: 10.13474/j.cnki.11-2246.2019.0376

• 人工智能与高精度地图 • 上一篇下一篇

激光SLAM移动机器人室内定位研究

严小意, 郭杭

南昌大学信息工程学院, 江西南昌 330031

收稿日期:2019-03-06 修回日期:2019-04-15 发布日期:2020-01-03
作者简介:严小意(1993-),男,硕士生,主要从事室内定位方面的研究。E-mail:1091499253@qq.com
基金资助:
国家重点研发计划（2016YB0502002）；国家自然科学基金（41764002）

Research on indoor positioning of LiDAR SLAM mobile robot

YAN Xiaoyi, GUO Hang

College of Information Engineering, Nanchang University, Nanchang 330031, China

Received:2019-03-06 Revised:2019-04-15 Published:2020-01-03

摘要/Abstract

摘要： 针对目前室内移动导航定位精度低和累积误差大的问题，提出了一种激光雷达（LiDAR）和惯性测量单元（IMU）相融合的导航定位系统。首先，该方法是从LiDAR扫描测量中提取环境特征和构建地图，然后，由IMU采集的姿态信息通过卡尔曼滤波，补偿由于LiDAR扫描引起的位置和姿态输出的误差，以提高机器人移动的定位精度。试验结果表明，该方法可以提高室内移动机器人定位和构建地图的精度和稳健性。

关键词: 室内导航, 激光雷达, 惯性测量单元, 卡尔曼滤波, 组合导航

Abstract: Aiming at the low accuracy and cumulative error of indoor mobile navigation, a fusion navigation system based on light detection and ranging (LiDAR) and inertial measurement unit (IMU) is proposed. First, the method extracts environmental features and constructs maps from LiDAR scan measurements. Then, the pose information collected by the IMU compensates for the position and attitude output errors caused by LiDAR scans by Kalman filtering to improve the positioning of the robot movement precision. The experimental results show that the method can improve the accuracy and robustness of indoor mobile robot positioning and map construction.

Key words: indoor navigation, LiDAR, IMU, Kalman filter, integrated navigation

中图分类号:

严小意, 郭杭. 激光SLAM移动机器人室内定位研究[J]. 测绘通报, 2019, 0(12): 8-11.

YAN Xiaoyi, GUO Hang. Research on indoor positioning of LiDAR SLAM mobile robot[J]. Bulletin of Surveying and Mapping, 2019, 0(12): 8-11.

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激光SLAM移动机器人室内定位研究

Research on indoor positioning of LiDAR SLAM mobile robot

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