A Fast Dynamic Point Detection Method for LiDAR-Inertial Odometry in Driving Scenarios
Abstract
Existing 3D point-based dynamic point detection and removal methods have a significant time overhead, making them difficult to adapt to LiDAR-inertial odometry systems. This paper proposes a label consistency based dynamic point detection and removal method for handling moving vehicles and pedestrians in autonomous driving scenarios, and embeds the proposed dynamic point detection and removal method into a self-designed LiDAR-inertial odometry system. Experimental results on three public datasets demonstrate that our method can accomplish the dynamic point detection and removal with extremely low computational overhead (i.e., 1$\sim$9ms) in LIO systems, meanwhile achieve comparable preservation rate and rejection rate to state-of-the-art methods and significantly enhance the accuracy of pose estimation. We have released the source code of this work for the development of the community.
- Publication:
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arXiv e-prints
- Pub Date:
- July 2024
- DOI:
- 10.48550/arXiv.2407.03590
- arXiv:
- arXiv:2407.03590
- Bibcode:
- 2024arXiv240703590Y
- Keywords:
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- Computer Science - Robotics
- E-Print:
- 8 pages, submitted to RA-L