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3. [UAV Avoiding Dynamic Obstacles](https://github.com/hku-mars/dyn_small_obs_avoidance): One of the implementation of FAST-LIO in robot's planning.
4. [R2LIVE](https://github.com/hku-mars/r2live): A high-precision LiDAR-inertial-Vision fusion work using FAST-LIO as LiDAR-inertial front-end.
5. [UGV Demo](https://www.youtube.com/watch?v=wikgrQbE6Cs): Model Predictive Control for Trajectory Tracking on Differentiable Manifolds.
-6. [SC-A-LOAM](https://github.com/gisbi-kim/SC-A-LOAM#for-livox-lidar): A [Scan-Context](https://github.com/irapkaist/scancontext) loop closure module that can directly work with FAST-LIO.
+6. [FAST-LIO-SLAM](https://github.com/gisbi-kim/FAST_LIO_SLAM): The integration of FAST-LIO with [Scan-Context](https://github.com/irapkaist/scancontext) **loop closure** module.
## FAST-LIO
**FAST-LIO** (Fast LiDAR-Inertial Odometry) is a computationally efficient and robust LiDAR-inertial odometry package. It fuses LiDAR feature points with IMU data using a tightly-coupled iterated extended Kalman filter to allow robust navigation in fast-motion, noisy or cluttered environments where degeneration occurs. Our package address many key issues:
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-**Related video:** [FAST-LIO2](https://youtu.be/2OvjGnxszf8), [FAST-LIO1](https://youtu.be/iYCY6T79oNU), [FAST-LIO1 + Scan-context loop closure](https://youtu.be/Fw9S6D6HozA)
+**Related video:** [FAST-LIO2](https://youtu.be/2OvjGnxszf8), [FAST-LIO1](https://youtu.be/iYCY6T79oNU), [FAST-LIO2 + Scan-context Loop Closure](https://www.youtube.com/watch?v=nu8j4yaBMnw)
**Pipeline:**