The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Tightly-Coupled GNSS-LiDAR-Inertial State Estimator for Mapping and Autonomous Driving

비정형 환경 내 지도 작성과 자율주행을 위한 GNSS-라이다-관성 상태 추정 시스템

  • Hyeonjae Gil (Mechanical Engineering, Seoul National University) ;
  • Dongjae Lee (Mechanical Engineering, Seoul National University) ;
  • Gwanhyeong Song (Mechanical Engineering, Seoul National University) ;
  • Seunguk Ahn (Advanced Technology Team, Hanwha Aerospace) ;
  • Ayoung Kim (Mechanical Engineering, Seoul National University)
  • Received : 2022.10.31
  • Accepted : 2022.12.16
  • Published : 2023.02.28
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Abstract

We introduce tightly-coupled GNSS-LiDAR-Inertial state estimator, which is capable of SLAM (Simultaneously Localization and Mapping) and autonomous driving. Long term drift is one of the main sources of estimation error, and some LiDAR SLAM framework utilize loop closure to overcome this error. However, when loop closing event happens, one's current state could change abruptly and pose some safety issues on drivers. Directly utilizing GNSS (Global Navigation Satellite System) positioning information could help alleviating this problem, but accurate information is not always available and inaccurate vertical positioning issues still exist. We thus propose our method which tightly couples raw GNSS measurements into LiDAR-Inertial SLAM framework which can handle satellite positioning information regardless of its uncertainty. Also, with NLOS (Non-light-of-sight) satellite signal handling, we can estimate our states more smoothly and accurately. With several autonomous driving tests on AGV (Autonomous Ground Vehicle), we verified that our method can be applied to real-world problem.

Keywords

Acknowledgement

This project was funded and supported by the grant from Hanwha Aerospace as part of the development of 3D SLAM technology for unstructured environment.

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