mlsanityData to 7 Oct 2026

Tightly Coupled 3D Lidar Inertial Odometry and Mapping

arXiv 1904.06993 ↗First posted 15 Apr 2019cs.RO cs.CVcited by 34

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Abstract (arXiv)

Ego-motion estimation is a fundamental requirement for most mobile robotic applications. By sensor fusion, we can compensate the deficiencies of stand-alone sensors and provide more reliable estimations. We introduce a tightly coupled lidar-IMU fusion method in this paper. By jointly minimizing the cost derived from lidar and IMU measurements, the lidar-IMU odometry (LIO) can perform well with acceptable drift after long-term experiment, even in challenging cases where the lidar measurements can be degraded. Besides, to obtain more reliable estimations of the lidar poses, a rotation-constrained refinement algorithm (LIO-mapping) is proposed to further align the lidar poses with the global map. The experiment results demonstrate that the proposed method can estimate the poses of the sensor pair at the IMU update rate with high precision, even under fast motion conditions or with insufficient features.

Key facts. Cited by 34 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Apr 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 6; 2023: 5; 2024: 4; 2025: 8; 2026: 2.

34 papers.

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  1. 2021DSEC: A Stereo Event Camera Dataset for Driving Scenarioscited by 297
  2. 2021NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challengecited by 32
  3. 2021MULLS: Versatile LiDAR SLAM via Multi-metric Linear Least Squarecited by 27
  4. 2022Situational Graphs for Robot Navigation in Structured Indoor Environmentscited by 21
  5. 2021Greedy-Based Feature Selection for Efficient LiDAR SLAMcited by 9
  6. 2021Real-time Multi-Adaptive-Resolution-Surfel 6D LiDAR Odometry using Continuous-time Trajectory Optimizationcited by 9
  7. 2023Milestones in Autonomous Driving and Intelligent Vehicles Part II: Perception and Planningcited by 9
  8. 2025Ev-3DOD: Pushing the Temporal Boundaries of 3D Object Detection with Event Camerascited by 8
  9. 2022Intensity Image-based LiDAR Fiducial Marker Systemcited by 4
  10. 2023TransFusionOdom: Interpretable Transformer-based LiDAR-Inertial Fusion Odometry Estimationcited by 4
  11. 2023Learning Parallax for Stereo Event-based Motion Deblurringcited by 4
  12. 2021MFuseNet: Robust Depth Estimation with Learned Multiscopic Fusioncited by 3
22 more
  1. 2022R3LIVE++: A Robust, Real-time, Radiance reconstruction package with a tightly-coupled LiDAR-Inertial-Visual state Estimatorcited by 3
  2. 2022FP-Loc: Lightweight and Drift-free Floor Plan-assisted LiDAR Localizationcited by 2
  3. 2024Traj-LIO: A Resilient Multi-LiDAR Multi-IMU State Estimator Through Sparse Gaussian Processcited by 2
  4. 2026FMCW-LIO: A Doppler LiDAR-Inertial Odometrycited by 2
  5. 2023HybridFusion: LiDAR and Vision Cross-Source Point Cloud Fusioncited by 1
  6. 2024Monocular Localization with Semantics Map for Autonomous Vehiclescited by 1
  7. 2024Reliable-loc: Robust sequential LiDAR global localization in large-scale street scenes based on verifiable cuescited by 1
  8. 2021AR Mapping: Accurate and Efficient Mapping for Augmented Realitycited by 0
  9. 20213D Surfel Map-Aided Visual Relocalization with Learned Descriptorscited by 0
  10. 2021SmartDepthSync: Open Source Synchronized Video Recording System of Smartphone RGB and Depth Camera Range Image Frames with Sub-millisecond Precisioncited by 0
  11. 2022LMBAO: A Landmark Map for Bundle Adjustment Odometry in LiDAR SLAMcited by 0
  12. 2022A Tightly Coupled LiDAR-IMU Odometry through Iterated Point-Level Undistortioncited by 0
  13. 2023Perception-and-Energy-aware Motion Planning for UAV using Learning-based Model under Heteroscedastic Uncertaintycited by 0
  14. 2024AscDAMs: Advanced SLAM-based channel detection and mapping systemcited by 0
  15. 2025Universal Online Temporal Calibration for Optimization-based Visual-Inertial Navigation Systemscited by 0
  16. 2025KN-LIO: Geometric Kinematics and Neural Field Coupled LiDAR-Inertial Odometrycited by 0
  17. 2025Deep Neural Networks for Accurate Depth Estimation with Latent Space Featurescited by 0
  18. 2025CAR-LOAM: Color-Assisted Robust LiDAR Odometry and Mappingcited by 0
  19. 2025Incorporating GNSS Information with LIDAR-Inertial Odometry for Accurate Land-Vehicle Localizationcited by 0
  20. 2025Dense-depth map guided deep Lidar-Visual Odometry with Sparse Point Clouds and Imagescited by 0
  21. 2025DCReg: Decoupled Characterization for Efficient Degenerate LiDAR Registrationcited by 0
  22. 2026The Coastline as a Structural Constraint: Harnessing Scene Geometry for Autonomous Surface Vessel Localizationcited by 0