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LTA-OM: Long-Term Association LiDAR-IMU Odometry and Mapping
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  • zuhao zou,
  • Chongjian Yuan,
  • Wei Xu,
  • Haotian Li,
  • Liang Li,
  • Fu Zhang
zuhao zou
The University of Hong Kong Department of Mechanical Engineering

Corresponding Author:zuhao.zou@connect.hku.hk

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Chongjian Yuan
The University of Hong Kong Department of Mechanical Engineering
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Wei Xu
The University of Hong Kong Department of Mechanical Engineering
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Haotian Li
The University of Hong Kong Department of Mechanical Engineering
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Liang Li
The University of Hong Kong Department of Mechanical Engineering
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Fu Zhang
The University of Hong Kong Department of Mechanical Engineering
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Abstract

Simultaneous localization and mapping (SLAM) technology is ubiquitously employed in ground robots, unmanned aerial vehicles, and autonomous cars. This paper presents LTA-OM: an efficient, robust, and accurate LiDAR SLAM system. Employing FAST-LIO2 and Stable Triangle Descriptor as LiDAR-IMU odometry and the loop detection method, respectively, LTA-OM is implemented to be functionally complete, including loop detection and correction, false positive loop closure rejection, long-term association mapping, and multi-session localization and mapping. One novelty of this paper is the real-time long-term association (LTA) mapping, which exploits the direct scan-to-map registration of FAST-LIO2 and employs the corrected history map to constrain the mapping process globally. LTA leads to more globally consistent map construction and drift-less odometry at revisit places. We exhaustively benchmark LTA-OM and other state-of-the-art LiDAR systems with 18 data sequences. The results show that LTA-OM steadily outperforms other systems regarding trajectory accuracy, map consistency, and time consumption. The robustness of LTA-OM is validated in a challenging scene - a multi-level building having similar structures at different levels. Besides, a multi-session mode is designed to allow the user to store current session’s results, including the corrected map points, optimized odometry, and descriptor database for future sessions. The benefits of this mode are additional accuracy improvement and consistent map stitching, which is helpful for life-long mapping. Furthermore, LTA-OM has valuable features for robot control and path planning, including high-frequency and real-time odometry, drift-less odometry at revisit places, and fast loop closing convergence. Moreover, LTA-OM is versatile as it is applicable to both multi-line spinning and solid-state LiDARs, mobile robots and handheld platforms.
06 Mar 2023Submitted to Journal of Field Robotics
06 Mar 2023Submission Checks Completed
06 Mar 2023Assigned to Editor
17 Mar 2023Review(s) Completed, Editorial Evaluation Pending
10 May 2023Reviewer(s) Assigned
05 Sep 2023Editorial Decision: Revise Major
06 Nov 20231st Revision Received
30 Jan 2024Reviewer(s) Assigned
28 Feb 2024Review(s) Completed, Editorial Evaluation Pending
20 Mar 2024Editorial Decision: Accept