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Loosely-coupled lidar-inertial odometry and mapping in real time

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Abstract

The lidar-inertial-based simultaneous localization and mapping (SLAM) have been widely investigated in recent years. In this paper, a loosely-coupled lidar-inertial odometry and mapping method is developed for robot state estimation in real-time. The proposed lidar-inertial odometry is a loosely-coupled and nonlinear optimization-based method, fusing IMU measurements and pose of lidar odometry. Lidar odometry processing de-skewed point cloud with keyframes strategy, which significantly saves computation and allows scan matching run in real-time. Further, high-frequency robot state is obtained by imu prediction in a short time. And a sliding-window-based optimization is preformed to correct imu prediction in time. Real-world experiments and public dataset tests are performed in different scenarios to validate accuracy and effectiveness of our method.

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Funding

This work was supported in part by the National Key Research and Development Program of China under Grant 2018AAA0102401, the National Natural Science Foundation of China under Grant 62022060, 61773278, 61873340,61903349, 62073234 and 62003236 and the Basic Planning To strengthen key basic research projects (011DY2005211285002Z001).

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Tianjin University, Tianjin, China

    Guohui Xie, Qun Zong, Xuewei Zhang & Bailing Tian

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  1. Guohui Xie
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  2. Qun Zong
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  3. Xuewei Zhang
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  4. Bailing Tian
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Correspondence to Bailing Tian.

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Xie, G., Zong, Q., Zhang, X. et al. Loosely-coupled lidar-inertial odometry and mapping in real time. Int J Intell Robot Appl 5, 119–129 (2021). https://doi.org/10.1007/s41315-021-00164-5

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  • DOI: https://doi.org/10.1007/s41315-021-00164-5

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