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Open AccessArticle

Robust GICP-Based 3D LiDAR SLAM for Underground Mining Environment

by Zhuli Ren 1,2,*, Liguan Wang 1,2 and Lin Bi 1,2,*
1
School of Resources and Safety Engineering, Central South University, Changsha 410083, China
2
Digital Mine Research Center, Central South University, Changsha 410083, China
*
Authors to whom correspondence should be addressed.
Sensors 2019, 19(13), 2915; https://doi.org/10.3390/s19132915
Received: 15 May 2019 / Revised: 25 June 2019 / Accepted: 26 June 2019 / Published: 1 July 2019
(This article belongs to the Collection Positioning and Navigation)
Unmanned mining is one of the most effective methods to solve mine safety and low efficiency. However, it is the key to accurate localization and mapping for underground mining environment. A novel graph simultaneous localization and mapping (SLAM) optimization method is proposed, which is based on Generalized Iterative Closest Point (GICP) three-dimensional (3D) point cloud registration between consecutive frames, between consecutive key frames and between loop frames, and is constrained by roadway plane and loop. GICP-based 3D point cloud registration between consecutive frames and consecutive key frames is first combined to optimize laser odometer constraints without other sensors such as inertial measurement unit (IMU). According to the characteristics of the roadway, the innovative extraction of the roadway plane as the node constraint of pose graph SLAM, in addition to automatic removing the noise point cloud to further improve the consistency of the underground roadway map. A lightweight and efficient loop detection and optimization based on rules and GICP is designed. Finally, the proposed method was evaluated in four scenes (such as the underground mine laboratory), and compared with the existing 3D laser SLAM method (such as Lidar Odometry and Mapping (LOAM)). The results show that the algorithm could realize low drift localization and point cloud map construction. This method provides technical support for localization and navigation of underground mining environment. View Full-Text
Keywords: underground mine; SLAM; GICP; graph optimization; roadway plane; loop detection underground mine; SLAM; GICP; graph optimization; roadway plane; loop detection
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MDPI and ACS Style

Ren, Z.; Wang, L.; Bi, L. Robust GICP-Based 3D LiDAR SLAM for Underground Mining Environment. Sensors 2019, 19, 2915.

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