feat: Add MARS-LVIG dataset details and documentation

README.md

@@ -24,6 +24,11 @@ Our collection includes two major robotics datasets:
 - **Scenarios**: HKU campus sequences, indoor buildings, outdoor environments  
 - **Applications**: Photorealistic 3D reconstruction, real-time dense mapping
 
+### 🛰️ [MARS-LVIG Dataset](./mars_lvig/)
+- **Focus**: Multi-sensor SLAM with LiDAR-Visual-Inertial-GNSS fusion
+- **Scenarios**: Diverse outdoor environments with GNSS integration
+- **Applications**: Robust state estimation, multi-sensor fusion, GNSS-aided navigation
+
 ## Key Features
 
 - **Standardized Format**: All datasets converted to MCAP for consistent processing
@@ -42,7 +47,7 @@ These MCAP files can be processed using standard robotics tools and libraries th
 
 ### Recommended Tools
 - [ros2mcap](https://github.com/DapengFeng/ros2mcap) - ROS 1 MCAP support
-- [MCAP CLI](https://mcap.dev/docs/cli) - Command-line tools for MCAP manipulation
+- [MCAP CLI](https://mcap.dev/guides/cli) - Command-line tools for MCAP manipulation
 - [Foxglove Studio](https://foxglove.dev/) - Visualization and analysis platform
 - [ROS 2](https://docs.ros.org/en/humble/Concepts/About-ROS-Interfaces.html) - Robot Operating System with MCAP support
 

mars_lvig/README.md

@@ -0,0 +1,31 @@
+# [MARS-LVIG Dataset](https://mars.hku.hk/dataset.html)
+
+This dataset contains MCAP files for the MARS-LVIG (Multi-sensor SLAM with Accurate and Robust State estimation using LiDAR-Visual-Inertial-GNSS) system, designed for robust multi-modal sensor fusion research.
+
+## Dataset Overview
+
+MARS-LVIG focuses on accurate and robust state estimation by fusing multiple sensor modalities including LiDAR, visual cameras, inertial measurements, and GNSS signals. This dataset provides comprehensive sensor data for developing and evaluating advanced SLAM algorithms in diverse environments.
+
+## Key Features
+
+- **Multi-sensor fusion**: LiDAR, camera, IMU, and GNSS data streams
+- **Robust state estimation**: Designed for challenging scenarios with sensor degradation
+- **Accurate localization**: High-precision ground truth for algorithm evaluation
+- **Diverse environments**: Various outdoor scenarios
+
+## Sensor Configuration
+
+- **LiDAR**: High-resolution 3D point cloud measurements
+- **Camera**: Visual imagery for feature-based tracking
+- **IMU**: High-frequency inertial measurements
+- **GNSS**: Global positioning data where available
+- **Synchronization**: Hardware-synchronized multi-modal data streams
+
+## Applications
+
+This dataset is ideal for:
+- Multi-sensor SLAM algorithm development
+- Robust state estimation research
+- Sensor fusion and calibration studies
+- GNSS-aided navigation system evaluation
+- Outdoor localization and mapping