LOG-LIO2: A LiDAR-Inertial Odometry With Efficient Uncertainty Analysis
Author:
Affiliation:
1. School of Surveying and Geo-Informatics, Tongji University, Shanghai, China
2. Department of Computer Science and Technology, School of Electronics and Information Engineering, Tongji University, Shanghai, China
Funder
National Key Research and Development Program of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/7083369/10638067/10631658.pdf?arnumber=10631658
Reference12 articles.
1. State Estimation for Robotics
2. Pixel-Level Extrinsic Self Calibration of High Resolution LiDAR and Camera in Targetless Environments
3. A LiDAR-inertial Odometry with Principled Uncertainty Modeling
4. BALM: Bundle Adjustment for Lidar Mapping
5. Efficient and Probabilistic Adaptive Voxel Mapping for Accurate Online LiDAR Odometry
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