LIV-GaussMap: LiDAR-Inertial-Visual Fusion for Real-time 3D Radiance Field Map Rendering

Overview

Hardware platform

https://github.com/sheng00125/LIV_handhold

LIV-GaussMap: LiDAR-Inertial-Visual Fusion for Real-time 3D Radiance Field Map Rendering

IEEE Robotics and Automation Letters, 2024.

Features

• Real-time fusion of LiDAR, IMU, and camera data.
• High-performance 3D radiance field map rendering.

Demo on public dataset of HKU:

Demo on our self-collect dataset:

Dependencies

The following libraries and tools are required to run the project:

• ROS (Robot Operating System)
• PCL (Point Cloud Library)
• OpenCV
• Eigen3
• Ceres Solver

To install dependencies, you can use the following command for Ubuntu:

sudo apt-get install 

Datasets

Installation

1. Clone the repository:

git clone [email protected]:sheng00125/LIV-GaussMap.git
cd LIV-GaussMap

2. Build the project using catkin:

catkin_make
source devel/setup.bash

Usage

1. Launch the main application:

If you find this work useful, please consider citing our paper:

@article{hong2024liv,
  title={LIV-GaussMap: LiDAR-Inertial-Visual Fusion for Real-time 3D Radiance Field Map Rendering},
  author={Hong, Sheng and et al.},
  journal={IEEE Robotics and Automation Letters},
  year={2024},
  publisher={IEEE}
}

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For any inquiries or questions, feel free to open an issue or contact the authors of the paper.