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PlanarMesh: Building Compact 3D Meshes from LiDAR using Incremental Adaptive Resolution Reconstruction

  • Jiahao Wang
  • , Nived Chebrolu
  • , Yifu Tao
  • , Lintong Zhang
  • , Ayoung Kim
  • , Maurice Fallon

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Building an online 3D LiDAR mapping system that produces a detailed surface reconstruction while remaining computationally efficient is a challenging task. In this paper, we present PlanarMesh, a novel incremental, mesh-based LiDAR reconstruction system that adaptively adjusts mesh resolution to achieve compact, detailed reconstructions in real-time. It introduces a new representation, planar-mesh, which combines plane modeling and meshing to capture both large surfaces and detailed geometry. The planar-mesh can be incrementally updated considering both local surface curvature and free-space information from sensor measurements. We employ a multi-threaded architecture with a Bounding Volume Hierarchy (BVH) for efficient data storage and fast search operations, enabling real-time performance. Experimental results show that our method achieves reconstruction accuracy on par with, or exceeding, state-of-the-art techniques - including truncated signed distance functions, occupancy mapping, and voxel-based meshing - while producing smaller output file sizes (10 times smaller than raw input and more than 5 times smaller than mesh-based methods) and maintaining real-time performance (around 2 Hz for a 64-beam sensor).

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.
Pages15726-15733
Number of pages8
ISBN (Electronic)9798331543938
DOIs
Publication statusPublished - Nov 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

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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