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@@ -77,7 +77,7 @@ Thanks Jialin Liu (Fudan University) for his work to test LVI-SAM on M2DGR. Foll
1. A rich pool of sensory information including vision, lidar, IMU, GNSS,event, thermal-infrared images and so on
2. Various scenarios in real-world environments including lifts, streets, rooms, halls and so on.
3. Our dataset brings great challenge to existing SLAM algorithms including LIO-SAM and ORB-SLAM3. If your proposed algorihm outperforms SOTA systems on M2DGR, your paper will be much more convincing and valuable.
4. A lot of excellent projects have been tested on M2DGR/M2DGE-plus, for examples, Ground-Fusion, Swarm-SLAM, DAMS-LIO, VoxelMap++, GRIL-Cali, and so on!
4. A lot of excellent projects have been tested on M2DGR/M2DGE-plus, for examples, [Ground-Fusion](https://github.com/SJTU-ViSYS/Ground-Fusion), [Swarm-SLAM](https://github.com/MISTLab/Swarm-SLAM), DAMS-LIO, [VoxelMap++](https://github.com/uestc-icsp/VoxelMapPlus_Public), [GRIL-Cali](https://github.com/SJTU-ViSYS/Ground-Fusion), and so on!
