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add the intro of initiallization and bubble planner
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XW-HKU authored Jul 4, 2022
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## Related Works
**Control and Planning**
## Related Works and Extended Application

**SLAM:**

1. [ikd-Tree](https://github.com/hku-mars/ikd-Tree): A state-of-art dynamic KD-Tree for 3D kNN search.
2. [IKFOM](https://github.com/hku-mars/IKFoM): A Toolbox for fast and high-precision on-manifold Kalman filter.
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. [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.
7. [FAST-LIO-LOCALIZATION](https://github.com/HViktorTsoi/FAST_LIO_LOCALIZATION): The integration of FAST-LIO with **Re-localization** function module.
<!-- 8. [**Robust and Online LiDAR-inertial Initialization**](https://github.com/hku-mars/LiDAR_IMU_Init): Extrinsic and temporal initiallization for LIO.
9. [**Bubble Planner**](https://arxiv.org/abs/2202.12177): Planning High-speed Smooth Quadrotor Trajectories using Receding Corridors.
10. [**FAST-LIVO**](https://github.com/hku-mars/FAST-LIVO): Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry. -->
2. [R2LIVE](https://github.com/hku-mars/r2live): A high-precision LiDAR-inertial-Vision fusion work using FAST-LIO as LiDAR-inertial front-end.
3. [LI_Init](https://github.com/hku-mars/LiDAR_IMU_Init): A robust, real-time LiDAR-IMU extrinsic initialization and synchronization package..
4. [FAST-LIO-LOCALIZATION](https://github.com/HViktorTsoi/FAST_LIO_LOCALIZATION): The integration of FAST-LIO with **Re-localization** function module.

**Control and Plan:**

1. [IKFOM](https://github.com/hku-mars/IKFoM): A Toolbox for fast and high-precision on-manifold Kalman filter.
2. [UAV Avoiding Dynamic Obstacles](https://github.com/hku-mars/dyn_small_obs_avoidance): One of the implementation of FAST-LIO in robot's planning.
3. [UGV Demo](https://www.youtube.com/watch?v=wikgrQbE6Cs): Model Predictive Control for Trajectory Tracking on Differentiable Manifolds.
4. [Bubble Planner](https://arxiv.org/abs/2202.12177): Planning High-speed Smooth Quadrotor Trajectories using Receding Corridors.

<!-- 10. [**FAST-LIVO**](https://github.com/hku-mars/FAST-LIVO): Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry. -->

## 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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<img src="doc/ulhkwh_fastlio.gif" width = 49.6% >
</div>

**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)
**Related video:** [FAST-LIO2](https://youtu.be/2OvjGnxszf8), [FAST-LIO1](https://youtu.be/iYCY6T79oNU)

**Pipeline:**
<div align="center">
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