Update README.md

README.md

@@ -22,10 +22,10 @@ First Author: [**Jie Yin 殷杰**](https://github.com/sjtuyinjie?tab=repositorie
 
 
 ## 🎯 NOTICE
-### We strongly recommend that the newly proposed SLAM algorithm be tested on our M2DGR / M2DGR-plus benchmark, because our data has following features:
+### We strongly recommend that the newly proposed SLAM algorithm be tested on our [M2DGR](https://github.com/SJTU-ViSYS/M2DGR) / [M2DGR-plus](https://github.com/SJTU-ViSYS/M2DGR-plus) / [Ground-Challenge](https://github.com/sjtuyinjie/Ground-Challenge) benchmark, because our data has following features:
 1. **Rich 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](https://github.com/TixiaoShan/LIO-SAM) and [ORB-SLAM3](https://github.com/UZ-SLAMLab/ORB_SLAM3). If your proposed algorihm outperforms SOTA systems on [M2DGR](https://github.com/SJTU-ViSYS/M2DGR)/[M2DGR-plus](https://github.com/SJTU-ViSYS/M2DGR-plus), your paper will be much more convincing and valuable.
+3. Our dataset brings **great challenge** to existing SLAM algorithms including [LIO-SAM](https://github.com/TixiaoShan/LIO-SAM) and [ORB-SLAM3](https://github.com/UZ-SLAMLab/ORB_SLAM3). If your proposed algorihm outperforms SOTA systems on our benchmark, your paper will be much more convincing and valuable.
 4. 🔥 A lot of excellent **open-source** projects have been built on M2DGR/M2DGE-plus, for examples, [Ground-Fusion](https://github.com/SJTU-ViSYS/Ground-Fusion), [Log-LIO](https://github.com/tiev-tongji/LOG-LIO), [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), [LINK3d](https://github.com/YungeCui/LinK3D), [i-Octree](https://github.com/zhujun3753/i-octree), [LIO-EKF](https://github.com/YibinWu/LIO-EKF) and so on!