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An Efficient Scan-to-Map Matching Approach Based on Multi-channel Lidar

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Abstract

Accurately localizing the vehicle against a pre-built high precision map is an essential step for the Autonomous Land Vehicle (ALV). This paper proposes an efficient scan-to-map matching approach based on multi-channel lidar. We firstly advocate the usage of both the lidar reflectance map and the height map, as these two maps contain complementary information. Then, borrowing ideas from the Lucas-Kanade optical flow approach, we formulate the scan-to-map matching problem in a similar form, and propose an efficient gradient descent approach to solve it. Finally, the proposed approach is integrated into a filtering framework for real-time online localization. Experiments on real-world dataset have demonstrated the validity of our approach.

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Acknowledgements

This authors would like to thank the National Natural Science Foundation of China for the funding of Grant 61503400.

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Authors and Affiliations

  1. College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, Hunan, 410073, People’s Republic of China

    Hao Fu, Rui Yu, Lei Ye, Tao Wu & Xin Xu

Authors
  1. Hao Fu
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  2. Rui Yu
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  3. Lei Ye
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  4. Tao Wu
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  5. Xin Xu
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Correspondence to Hao Fu.

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I certify that this manuscript is original and has not been published and will not be submitted elsewhere for publication while being considered by Journal of Intelligent & Robotic Systems. The study is not split up into several parts to increase the quantity of submissions and submitted to various journals or to one journal over time. No data have been fabricated or manipulated (including images) to support the conclusions. No data, text, or theories by others are presented as if they were our own. The submission has been received explicitly from all co-authors. And authors whose names appear on the submission have contributed sufficiently to the scientific work and therefore share collective responsibility and accountability for the results.

Conflict of interests

The authors declare that they have no conflict of interest. This article does not contain any studies with human participants or animals performed by any of the authors. Informed consent was obtained from all individual participants included in the study.

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Fu, H., Yu, R., Ye, L. et al. An Efficient Scan-to-Map Matching Approach Based on Multi-channel Lidar. J Intell Robot Syst 91, 501–513 (2018). https://doi.org/10.1007/s10846-017-0717-0

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  • DOI: https://doi.org/10.1007/s10846-017-0717-0

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