Research on indoor positioning of LiDAR SLAM mobile robot

doi:10.13474/j.cnki.11-2246.2019.0376

Abstract

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

CLC Number:

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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