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International Symposium on Neural Networks

ISNN 2020: Advances in Neural Networks – ISNN 2020 pp 154–163Cite as

Deep Point Cloud Odometry: A Deep Learning Based Odometry with 3D Laser Point Clouds

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12557))

Abstract

Deep learning-based methods have attracted more attention to the pose estimation research that plays a crucial role in location and navigation. How to directly predict the pose from the point cloud in a data-driven way remains an open question. In this paper, we present a deep learning-based laser odometry system that consists of a network pose estimation and a local map pose optimization. The network consumes the original 3D point clouds directly and predicts the relative pose from consecutive laser scans. A scan-to-map optimization is utilized to enhance the robustness and accuracy of the poses predicted by the network. We evaluated our system on the KITTI odometry dataset and verified the effectiveness of the proposed system.

Y. Zhuang—This work was supported in part by the National Natural Science Foundation of China under grant 61973049 and U1913201.

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Authors and Affiliations

  1. The School of Control Science and Engineering, Dalian University of Technology, Dalian, 116024, China

    Chi Li, Fei Yan & Yan Zhuang

  2. Information Science and Technology College, Dalian Maritime University, Dalian, 116026, Liaoning, China

    Yisha Liu

Authors
  1. Chi Li
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  2. Yisha Liu
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  3. Fei Yan
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  4. Yan Zhuang
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Corresponding author

Correspondence to Yan Zhuang .

Editor information

Editors and Affiliations

  1. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China

    Min Han

  2. School of Science, Harbin Institute of Technology, Weihai, China

    Sitian Qin

  3. School of Engineering and Applied Sciences, University of the District of Columbia, Washington, DC, USA

    Nian Zhang

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Li, C., Liu, Y., Yan, F., Zhuang, Y. (2020). Deep Point Cloud Odometry: A Deep Learning Based Odometry with 3D Laser Point Clouds. In: Han, M., Qin, S., Zhang, N. (eds) Advances in Neural Networks – ISNN 2020. ISNN 2020. Lecture Notes in Computer Science(), vol 12557. Springer, Cham. https://doi.org/10.1007/978-3-030-64221-1_14

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  • DOI: https://doi.org/10.1007/978-3-030-64221-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64220-4

  • Online ISBN: 978-3-030-64221-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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