GLIM: 3D range-inertial localization and mapping with GPU-accelerated scan matching factors-Reference-Cited by-同舟云学术

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GLIM: 3D range-inertial localization and mapping with GPU-accelerated scan matching factors

Published:2024-09 Issue: Volume:179 Page:104750
ISSN:0921-8890
Container-title:Robotics and Autonomous Systems
language:en
Short-container-title:Robotics and Autonomous Systems

Author:

Koide Kenji^ORCID,Yokozuka Masashi^ORCID,Oishi Shuji^ORCID,Banno Atsuhiko

Funder

New Energy and Industrial Technology Development Organization

Japan Society for the Promotion of Science

Publisher

Elsevier BV

Reference72 articles.

1. Low-drift and real-time LiDAR odometry and mapping;Zhang;Auton. Robots,2016

2. Tightly coupled 3D LiDAR inertial odometry and mapping;Ye,2019

3. LINS: A LiDAR-inertial state estimator for robust and efficient navigation;Qin,2020

4. Faster-LIO: Lightweight tightly coupled LiDAR-inertial odometry using parallel sparse incremental voxels;Bai;IEEE Robot. Automat. Lett.,2022

5. FAST-LIO2: Fast direct LiDAR-inertial odometry;Xu;IEEE Trans. Robot.,2022

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