Conference item
PlanarMesh: building compact 3D meshes from LiDAR using incremental adaptive resolution reconstruction
- 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 freespace 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).
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 7.3MB, Terms of use)
-
- Publisher copy:
- 10.1109/IROS60139.2025.11246204
Authors
+ UK Research and Innovation
More from this funder
- Funder identifier:
- https://ror.org/001aqnf71
- Grant:
- 10037847
- Publisher:
- IEEE
- Host title:
- 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- Pages:
- 15726-15733
- Publication date:
- 2025-11-27
- Acceptance date:
- 2025-07-01
- Event title:
- International Conference on Intelligent Robots and Systems (IROS 2025)
- Event location:
- Hangzhao, China
- Event website:
- https://www.iros25.org/
- Event start date:
- 2025-10-19
- Event end date:
- 2025-10-25
- DOI:
- EISSN:
-
2153-0866
- ISSN:
-
2153-0858
- EISBN:
- 9798331543938
- ISBN:
- 9798331543945
- Language:
-
English
- Keywords:
- Pubs id:
-
2290788
- Local pid:
-
pubs:2290788
- Deposit date:
-
2025-09-23
- ARK identifier:
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2025
- Rights statement:
- © 2025 IEEE
- Notes:
- This paper was presented at the The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
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