💎 Author: Jie Yin 殷杰

I'm an active open-source contributor interested on robotics and embodied AI, especially on reinforcement learning, dexterous manipulation, SLAM and arm plan and control. Welcome to follow me!

This is a curated list of resources relevant to LiDAR-Visual-Fusion-SLAM, which overviews over 35 top-tier publications on LiDAR-Visual fusion SLAM systems. I will keep updating this website from time to time. If this project is helpful for your research, please give me a star and fork, thanks! If your work about LiDAR-Visual-SLAM is accepted to top conferences or transactions, welcome to propose a issue and remind me of updating your work!

LiDAR-Visual SLAM combines the strengths of LiDAR and visual sensors to provide highly accurate and robust localization and mapping. This fusion leverages the precise distance measurements from LiDAR and the rich environmental details captured by cameras, resulting in enhanced performance in diverse and challenging environments. Below is a demo video of LiDAR-Visual-IMU SLAM system from SR LIVO, which shows the amazing performance of localization and mapping.

We encourage you to add your LiDAR-vision-fusion SLAM algorithms to this list!You can

• Submit a Pull Request to contribute new algorithms, configuration files, or improvements via Github Pull Request to post your paper and code

• 🔥 Ultra-Fusion: A Resilient Tightly-Coupled Multi-Sensor Fusion SLAM Framework under Sensor Degradation and Spatiotemporal Perturbation [code][dataset][website][video] (The system unifies WIO, VIO, LIO, and LVIO in one configurable optimization framework, with optional wheel/GNSS fusion and online calibration.)

• 🔥 [IJRR2026] Gaussian-LIC2: LiDAR-Inertial-Camera Gaussian Splatting SLAM [paper][code][website] (Real-time photo-realistic LIV SLAM with continuous-time trajectory optimization, zero-shot depth completion, and Gaussian-map-assisted odometry under LiDAR degeneration.)

• [RAL2026] Omni-LIVO: Robust RGB-Colored Multi-Camera Visual-Inertial-LiDAR Odometry via Photometric Migration and ESIKF Fusion [paper][code] (Extends FAST-LIVO2 to multi-camera settings with cross-view photometric migration and adaptive multi-view ESIKF fusion.)

• 🔥 [IROS2025] Towards Robust Sensor-Fusion Ground SLAM: A Comprehensive Benchmark and A Resilient Framework [paper][code][dataset] (A complete solution for SLAM under corner cases, including benchmark datasets and a resilient multi-sensor fusion SLAM framework)

• [ICRA2025] Gaussian-LIC: Real-Time Photo-Realistic SLAM with Gaussian Splatting and LiDAR-Inertial-Camera Fusion [paper][code][website] (Real-time LIV Gaussian Splatting SLAM with robust pose estimation and photo-realistic mapping in general outdoor scenarios.)

• 🔥 [TRO2025] GS-LIVO: Real-Time LiDAR, Inertial, and Visual Multisensor Fused Odometry With Gaussian Mapping [paper][code] (First real-time Gaussian-based LIVO deployable on embedded platforms such as Jetson Orin NX, with hash-indexed octree Gaussian maps and IESKF fusion.)

• [ICCV2025] GS-LIVM: Real-Time Photo-Realistic LiDAR-Inertial-Visual Mapping with Gaussian Splatting [paper][code] (Real-time outdoor LIV mapping with voxel Gaussian Process Regression and covariance-centered 3D Gaussian initialization.)

• [IROS2025] Intensity-Augmented LiDAR-Visual-Inertial Odometry and Meshing [paper]

• 🔥 [TRO2024] FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual Odometry [paper][code]

• 🔥 [TPAMI2024] R3LIVE++: A Robust, Real-time, Radiance reconstruction package with a tightly-coupled LiDAR-Inertial-Visual state Estimator [paper][code]

• [RAL2024] LIVER: A Tightly Coupled LiDAR-Inertial-Visual State Estimator With High Robustness for Underground Environments [paper]

• [RAL2024] A LiDAR-inertial-visual odometry and mapping system based on the sweep reconstruction method [paper][code]

• [RAL2024] Point-Line LIVO Using Patch-Based Gradient Optimization for Degenerate Scenes [paper][code] (Integrates visual point and line patches for robust localization in LiDAR-degenerate scenes.)

• [RAL2024] LVIO-Fusion:Tightly-Coupled LiDAR-Visual-Inertial Odometry and Mapping in Degenerate Environments [paper]

• [TIM2024] Dynam-LVIO: A Dynamic-Object-Aware LiDAR Visual Inertial Odometry in Dynamic Urban Environments [paper]

• [Remote Sensing2024] LVI-Fusion: A Robust Lidar-Visual-Inertial SLAM Scheme [paper]

• [TPAMI2023] SDV-LOAM: Semi-Direct Visual–LiDAR Odometry and Mapping [paper][code]

• [RAL2023] Coco-LIC: Continuous-Time Tightly-Coupled LiDAR-Inertial-Camera Odometry using Non-Uniform B-spline [paper][code]

• [TM2023] CR-LDSO: Direct Sparse LiDAR-Assisted Visual Odometry With Cloud Reusing [paper]

• [TM2023] Continuous-Time Fixed-Lag Smoothing for LiDAR-Inertial-Camera SLAM [paper]

• [IROS2022] Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry [paper][code]

• 🔥 [ICRA2022] R3LIVE: A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package [paper][code]

• [RAL2022] mvil-fusion: Monocular visual-inertial-lidar simultaneous localization and mapping in challenging environments [paper]

• 🔥 [RAL2021] R2LIVE: A Robust, Real-time, LiDAR-Inertial-Visual tightly-coupled state Estimator and mapping [paper][code]

• [IROS2021] Lvio-Fusion: A Self-adaptive Multi-sensor Fusion SLAM Framework Using Actor-critic Method [paper][code]

• [IROS2021] Super odometry: Imu-centric lidar-visual-inertial estimator for challenging environments [paper][code]

• [WACV2021] Self-Supervised Visual-LiDAR Odometry With Flip Consistency [paper][code]

• [ICRA2021] CamVox: A Low-cost and Accurate Lidar-assisted Visual SLAM System [paper][code]

• [ICRA2021] LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping [paper][code]

• [TIV2021] Efficient and Accurate Tightly-Coupled Visual-Lidar SLAM [paper]

• [ROBIO2021] LVIO-SAM: A Multi-sensor Fusion Odometry via Smoothing and Mapping [paper][code]

• [Remote Sensing2021] DV-LOAM: Direct Visual LiDAR Odometry and Mapping [paper][code]

• [IROS2020] LIC-Fusion 2.0: LiDAR-Inertial-Camera Odometry with Sliding-Window Plane-Feature Tracking [paper]

• [ICRA2020] Lidar-Monocular Visual Odometry using Point and Line Features [paper]

• [Automomous Robots2020] DVL-SLAM: sparse depth enhanced direct visual-LiDAR SLAM [paper]

• [IROS2019] LIC-Fusion: LiDAR-Inertial-Camera Odometry [paper]

• [IROS2019] ViLiVO: Virtual LiDAR-Visual Odometry for an Autonomous Vehicle with a Multi-Camera System [paper]

• [IROS2018] LIMO: Lidar-Monocular Visual Odometry [paper][code]

• [ICRA2015] Visual-lidar odometry and mapping: Low-drift, robust, and fast [paper]

• awesome-wheel-slam
• awesome-isaac-sim
• awesome-LiDAR-Camera-Calibration
• awesome-SLAM
• awesome-SLAM-datasets
• Awesome-Implicit-NeRF-Robotics
• awesome-humanoid-learning
• awesome-isaac-gym
• Awesome-Quadrupedal-Robots
• Awesome-Robot-Descriptions
• awesome-legged-locomotion-learning