mlsanityData to 7 Oct 2026

ImMesh: An Immediate LiDAR Localization and Meshing Framework

arXiv 2301.05206 ↗First posted 12 Jan 2023cs.RO cs.CVcited by 11

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Abstract (arXiv)

In this paper, we propose a novel LiDAR(-inertial) odometry and mapping framework to achieve the goal of simultaneous localization and meshing in real-time. This proposed framework termed ImMesh comprises four tightly-coupled modules: receiver, localization, meshing, and broadcaster. The localization module utilizes the prepossessed sensor data from the receiver, estimates the sensor pose online by registering LiDAR scans to maps, and dynamically grows the map. Then, our meshing module takes the registered LiDAR scan for incrementally reconstructing the triangle mesh on the fly. Finally, the real-time odometry, map, and mesh are published via our broadcaster. The key contribution of this work is the meshing module, which represents a scene by an efficient hierarchical voxels structure, performs fast finding of voxels observed by new scans, and reconstructs triangle facets in each voxel in an incremental manner. This voxel-wise meshing operation is delicately designed for the purpose of efficiency; it first performs a dimension reduction by projecting 3D points to a 2D local plane contained in the voxel, and then executes the meshing operation with pull, commit and push steps for incremental reconstruction of triangle facets. To the best of our knowledge, this is the first work in literature that can reconstruct online the triangle mesh of large-scale scenes, just relying on a standard CPU without GPU acceleration. To share our findings and make contributions to the community, we make our code publicly available on our GitHub: https://github.com/hku-mars/ImMesh.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 26 of its 107 references that are in the map. First posted on arXiv 12 Jan 2023.

Builds on

26 of 107 references.

References · 26

  1. 2017AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehiclescited by 517
  2. 2020TartanAir: A Dataset to Push the Limits of Visual SLAMcited by 494
  3. 2021NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Videocited by 241
  4. 2020Atlas: End-to-End 3D Scene Reconstruction from Posed Imagescited by 206
  5. 2019Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mappingcited by 181
  6. 2021FAST-LIO2: Fast Direct LiDAR-inertial Odometrycited by 170
  7. 2016Voxblox: Incremental 3D Euclidean Signed Distance Fields for On-Board MAV Planningcited by 148
  8. 2015On-Manifold Preintegration for Real-Time Visual-Inertial Odometrycited by 95
  9. 2020Flightmare: A Flexible Quadrotor Simulatorcited by 69
  10. 2022MeshLoc: Mesh-Based Visual Localizationcited by 62
  11. 2022A Survey on Metaverse: Fundamentals, Security, and Privacycited by 51
  12. 2021R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping packagecited by 49
14 more
  1. 2020FUEL: Fast UAV Exploration using Incremental Frontier Structure and Hierarchical Planningcited by 42
  2. 2019SurfelWarp: Efficient Non-Volumetric Single View Dynamic Reconstructioncited by 31
  3. 2018SurfelMeshing: Online Surfel-Based Mesh Reconstructioncited by 29
  4. 2022NTU VIRAL: A Visual-Inertial-Ranging-Lidar Dataset, From an Aerial Vehicle Viewpointcited by 28
  5. 2019Loam_livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoVcited by 27
  6. 2021MULLS: Versatile LiDAR SLAM via Multi-metric Linear Least Squarecited by 27
  7. 2022STD: Stable Triangle Descriptor for 3D place recognitioncited by 23
  8. 2020RAPTOR: Robust and Perception-aware Trajectory Replanning for Quadrotor Fast Flightcited by 20
  9. 2021Efficient and Probabilistic Adaptive Voxel Mapping for Accurate Online LiDAR Odometrycited by 16
  10. 2021R2LIVE: A Robust, Real-time, LiDAR-Inertial-Visual tightly-coupled state Estimator and mappingcited by 12
  11. 2019A fast, complete, point cloud based loop closure for LiDAR odometry and mappingcited by 9
  12. 2021ikd-Tree: An Incremental K-D Tree for Robotic Applicationscited by 9
  13. 2022R3LIVE++: A Robust, Real-time, Radiance reconstruction package with a tightly-coupled LiDAR-Inertial-Visual state Estimatorcited by 3
  14. 2022MARSIM: A light-weight point-realistic simulator for LiDAR-based UAVscited by 3

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Cited by year

Citing papers per year: 2023: 1; 2024: 5; 2025: 5.

11 papers.