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Intensity-Augmented LiDAR-Visual-Inertial Odometry and Meshing

  • Yun Feng Hua
  • , Qin Yu Liu
  • , Zhong Wei Lin
  • , Xiao Gong
  • , Bin Tao Zhao
  • , Jian Zhang
  • , Teng Fei Jiang
  • , Sheng Jun Shi
  • , Wei Wei Xu*
  • *Corresponding author for this work
  • Zhejiang University
  • Shining 3D
  • School of Mechatronics Engineering, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a tightly-coupled LiDAR-Visual-Inertial Odometry (LIVO) system that integrates both LIO and VIO subsystems. The system jointly estimates the state by fusing LiDAR or visual data with Inertial Measurement Units (IMUs). It employs point-to-mesh tracking to optimize LiDAR poses and leverages intensity information from LiDAR point clouds to refine camera pose estimation. The optimized camera pose, derived from VIO, plays a crucial role in texture mapping and 3D geometry synthesis (3DGS) rendering. Our experiments demonstrate a significant improvement in average Peak Signal-to-Noise Ratio (PSNR) compared to existing methods, including R3LIVE, SR-LIVO, and FAST-LIVO. Furthermore, the system features a real-time mapping module implemented on the GPU, utilizing Truncated Signed Distance Function (TSDF) fields for global map maintenance and the Marching Cubes algorithm for mesh extraction. This approach ensures rapid and precise tracking and reconstruction capabilities. Additionally, our system supports real-time remeshing of the global map upon detecting loop closures, thereby enhancing the robustness and accuracy of the overall SLAM process.

Original languageEnglish
Title of host publicationIROS 2025 - 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, Conference Proceedings
EditorsChristian Laugier, Alessandro Renzaglia, Nikolay Atanasov, Stan Birchfield, Grzegorz Cielniak, Leonardo De Mattos, Laura Fiorini, Philippe Giguere, Kenji Hashimoto, Javier Ibanez-Guzman, Tetsushi Kamegawa, Jinoh Lee, Giuseppe Loianno, Kevin Luck, Hisataka Maruyama, Philippe Martinet, Hadi Moradi, Urbano Nunes, Julien Pettre, Alberto Pretto, Tommaso Ranzani, Arne Ronnau, Silvia Rossi, Elliott Rouse, Fabio Ruggiero, Olivier Simonin, Danwei Wang, Ming Yang, Eiichi Yoshida, Huijing Zhao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5347-5354
Number of pages8
ISBN (Electronic)9798331543938
DOIs
StatePublished - 2025
Externally publishedYes
Event2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2025 - Hangzhou, China
Duration: 19 Oct 202525 Oct 2025

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2025
Country/TerritoryChina
CityHangzhou
Period19/10/2525/10/25

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