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Complex environment localization system using complementary ceiling and ground map information

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Abstract

This paper proposes a robust localization system using complementary information extracted from ceiling and ground plans, particularly applicable to dynamic and complex environments. The ceiling perception provides the robot with stable and time-invariant environmental features independent of the dynamic changes on the ground, whereas the ground perception allows the robot to navigate in the ground plane while avoiding stationary obstacles. We propose an architecture to fuse ground 2D LiDAR scan and ceiling 3D LiDAR scan with our enhanced mapping algorithm associating perception from both sources efficiently. The localization ability and the navigation performance can be promisingly secured even in a harsh environment with our complementary sensed information from the ground and ceiling. The salient feature of our work is that our system can simultaneously map both the ceiling and ground plane efficiently without extra efforts of deploying articulated landmarks and apply such hybrid information effectively, which facilitates the robot to travel through any indoor environment with human crowds without getting lost.

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Acknowledgements

The authors are deeply grateful to Zu Lin Ewe for his assistance with the additional experiments suggested by the reviewer. His contribution was instrumental in enhancing the quality and scope of this research.

Funding

This research was supported by the National Science and Technology Council of the Republic of China, and Center for Artificial Intelligence & Advanced Robotics, National Taiwan University, under the grant number MOST 111-2634-F-002-021 and MOST 111-2223-E-002-008.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan

    Chee-An Yu, Hao-Yun Chen & Chun-Chieh Wang

  2. NTU Center for Artificial Intelligence and Advanced Robotics, Taipei, Taiwan

    Li-Chen Fu

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  1. Chee-An Yu
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  2. Hao-Yun Chen
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  3. Chun-Chieh Wang
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Correspondence to Li-Chen Fu.

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Yu, CA., Chen, HY., Wang, CC. et al. Complex environment localization system using complementary ceiling and ground map information. Auton Robot 47, 669–683 (2023). https://doi.org/10.1007/s10514-023-10116-6

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