6 DOF Vehicle Pose Estimation Considering Lidar Odometry Initial Condition

  • Yang, Chanuk
  • Huh, Kunsoo
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초록

Precise localization is essential for reliable autonomous driving. Traditionally, many systems have turned to lane level map matching techniques utilizing High Definition Maps (HD-Maps). However, it is necessary to have considerate efforts tied to the continuous availability and timeliness of these HD-Maps. Taking this into account, this paper explores an alternative approach, focusing on landmark-based odometry and a filtering-based technique. The proposed localization algorithm is integrated with the GPS and the odometry in a loosely coupled approach. Also, the initial odometry rotation is estimated to improve the global consistency in localization. In addition, this method considers the change in vehicle speed and updates the landmark-based odometry, aiming to address the specific concerns like repetitive geometry scenarios such as in tunnels. Through experimental tests in normal scenarios and challenging scenarios like tunnels, it is demonstrated that our method offers certain benefits over the existing techniques.

키워드

OdometryLocation awarenessGlobal Positioning SystemLaser radarWheelsKalman filtersMathematical modelsPose estimation6-DOFLocalizationpose estimationlandmark-based odometryKalman filterinitializationLIO
제목
6 DOF Vehicle Pose Estimation Considering Lidar Odometry Initial Condition
저자
Yang, ChanukHuh, Kunsoo
DOI
10.1109/ACCESS.2024.3407680
발행일
2024-06
유형
Article
저널명
IEEE Access
12
페이지
77791 ~ 77799