π Interested in Embodied AI? Explore the UMI-3D Ecosystem
June 4, 2026 Β· View on GitHub
LIV-Eye: A Low-Cost LiDAR-Inertial-Visual Fusion 3D Sensor for Robotics and Embodied AI [δΈζ]
π Interested in Embodied AI? Explore the UMI-3D Ecosystem
π UMI-3D Project Homepage
| π§ UMI-3D Hardware | π°οΈ UMI-3D SLAM Pipeline | π€ UMI-3D Policy |
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| Hardware design, BOM, CAD, 3D-print parts | SLAM, synchronization, calibration, and data processing |
Policy training, deployment, inference π¦ Dataset & Models |
Table of Contents
- Highlights
- Repository Structure
- Bill of Materials (BOM)
- Assembly
- Wiring
- Driver Installation and Run
- LiDAR-Camera Joint Calibration
- Running FAST-LIVO2
- Platform Adaptability
- Acknowledgements
- License
Highlights
One sentence summary: A ~Β₯5000 (β $700) fully open-source hardware/software LiDAR-Inertial-Visual fusion perception kit. βοΈ Easy assembly, no soldering, one-click reproducibility. π³ Supports ROS1/ROS2 and Docker, π§ full calibration workflow (intrinsic/extrinsic/time sync), π§° compatible with FAST-LIVO2 algorithms, and delivers colored point cloud and odometry results in just 5 minutes.
Repository Structure
βββ FAST-LIVO2-Mid360-Config - The configuration and launch files of FAST-LIVO2 for the Mid-360 LiDAR
βββ liv_eye_cad - Solidworks files for LIV-Eye
βββ livox_ros_driver2 - Livox LiDAR ROS driver
βββ mvs_ros_driver - Hikvision Camera ROS driver
βββ README.md - Project homepage
βββ ...
Bill of Materials (BOM)
Target total cost: β Β₯5,000 (β $700, subject to actual purchase)
| Category | Model/Name | Reference Price | Image |
|---|---|---|---|
| LiDAR | Livox Mid-360 | Β₯3999 (β $560) | ![]() |
| Camera | Hikvision MV-CU013-A0UC | Β₯700 (β $100) | ![]() |
| Lens | Hikvision MVL-HF0628M-6MPE | Β₯150 (β $20) | ![]() |
| Wire | LiDAR-Camera Hardware Synchronizer | Β₯500 (β $70) | ![]() |
| Battery | 12V DC Battery | Β₯99 (β $15) | ![]() |
Assembly
Solidworks CAD files are provided in liv_eye_cad.
You can download and use them for 3D printing and assembly:
Wiring
The diagram below shows the complete wiring of LIV-Eye, in just six steps:
Note
If you do not need to use the LiDAR-Camera hardware synchronizer, please refer to the connection method and STM32 hardware synchronization solution in LIV_handhold.
Driver Installation and Run
-
Download and install MVS and Livox-SDK2. Set the camera to trigger mode in MVS.
-
Install the camera ROS driver mvs_ros_driver and launch in trigger mode:
roslaunch mvs_ros_driver mvs_camera_trigger.launch
- Install and launch the LiDAR ROS driver livox_ros_driver2:
roslaunch livox_ros_driver2 msg_MID360.launch
- Record sensor data:
rosbag record /livox/lidar /livox/imu /left_camera/image
Note
The mvs_ros_driver and livox_ros_driver2 are the same as those in LIV_handhold, and include modifications to support millisecond-level hardware synchronization.
LiDAR-Camera Joint Calibration
- Calibrate camera intrinsics. e.g. matlab.
- Use FAST-Calib for LiDARβcamera extrinsic calibration.
Running FAST-LIVO2
Install FAST-LIVO2. The configuration and launch files for the Mid-360 are provided in FAST-LIVO2-Mid360-Config. Update the intrinsic and extrinsic parameters to match your device, then run:
roslaunch fast_livo mapping_mid360.launch
This demo corresponds to the example LIV-Eye rosbag, which can be downloaded here.
Platform Adaptability
LIV-Eye is compact yet versatile! With its small form factor, standardized wiring, and open-source software, it can be seamlessly integrated into a wide range of robotic platforms to enable perception, navigation, and embodied AI research.
Acknowledgements
This project is based on the following open-source projects:
- Driver and time synchronization: LIV_handhold
- Calibration method: FAST-Calib
- Algorithm: FAST-LIVO2
- CAD Design: Link by pcl5
License
The source code is released under the GPLv2 license.
If you use this codebase in academic research, please cite any of the following papers:
[1] Zheng, Chunran, et al. "FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual Odometry."
[2] Zheng, Chunran, et al. "FAST-LIVO: Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry."
[3] Zheng, Chunran, et al. "FAST-Calib: LiDAR-Camera Extrinsic Calibration in One Second."
[4] Ziming, Wang, et al. "USTC FLICAR: A sensors fusion dataset of LiDAR-inertial-camera for heavy-duty autonomous aerial work robots."




