update readme

README.md

@@ -2,15 +2,15 @@
 
 A simple localization framework that can re-localize in built maps based on [FAST-LIO](https://github.com/hku-mars/FAST_LIO). 
 
-## Features
+## 1. Features
 - Realtime 3D global localization in a pre-built point cloud map. 
   By fusing low-frequency global localization (about 0.5~0.2Hz), and high-frequency odometry from FAST-LIO, the entire system is computationally efficient.
 
-<div align="center"><img src="doc/demo.GIF" width=100% /></div>
+<div align="center"><img src="doc/demo.GIF" width=90% /></div>
 
-- Eliminate the accumulative error of odometry.
+- Eliminate the accumulative error of the odometry.
 
-<div align="center"><img src="doc/demo_accu.GIF" width=100% /></div>
+<div align="center"><img src="doc/demo_accu.GIF" width=90% /></div>
 
 - The initial localization can be provided either by rough manual estimation from RVIZ, or pose from another sensor/algorithm.
 
@@ -22,14 +22,14 @@ A simple localization framework that can re-localize in built maps based on [FAS
 </div>
 
 
-## Prerequisites
-### 1.1 Dependencies for FAST-LIO
+## 2. Prerequisites
+### 2.1 Dependencies for FAST-LIO
 
-Technically, if you have built and run FAST-LIO before, you may skip this section.
+Technically, if you have built and run FAST-LIO before, you may skip section 2.1.
 
 This part of dependency is consistent with FAST-LIO, please refer to the documentation https://github.com/hku-mars/FAST_LIO#1-prerequisites
 
-### 1.2 Dependencies for localization module
+### 2.2 Dependencies for localization module
 
 - python 2.7
 
@@ -40,12 +40,12 @@ This part of dependency is consistent with FAST-LIO, please refer to the documen
 Notice that, if using **Ubuntu 18.04** with native **PCL 1.8**, there may be issue after installing **python-pcl** through pip,
   please refer to https://github.com/barrygxwan/Python-PCL-Ubuntu18.04, download the **.whl** file and then install.
 
-## 2. Build
+## 3. Build
 Clone the repository and catkin_make:
 
 ```
     cd ~/$A_ROS_DIR$/src
-    git clone https://github.com/hviktortsoi/FAST_LIO_LOCALIZATION.git
+    git clone https://github.com/HViktorTsoi/FAST_LIO_LOCALIZATION.git
     cd FAST_LIO_LOCALIZATION
     git submodule update --init
     cd ../..
@@ -57,8 +57,8 @@ Clone the repository and catkin_make:
   ```export PCL_ROOT={CUSTOM_PCL_PATH}```
 
 
-## 3. Run Localization
-### Sample Dataset
+## 4. Run Localization
+### 4.1 Sample Dataset
 
 Demo rosbag in a large underground garage: 
 [Baidu Pan (Code: ne8d)](https://pan.baidu.com/s/1ceBiIAUqHa1vY3QjWpxwNA);
@@ -67,9 +67,9 @@ Corresponding map: [Baidu Pan (Code: kw6f)](https://pan.baidu.com/s/1Yw4vY3kEK8x
 
 The map can be built using LIO-SAM or FAST-LIO-SLAM.
 
-### Run
+### 4.2 Run
 
-1. First, please make sure you're using **Python 2.7** environment;
+1. First, please make sure you're using a **Python 2.7** environment;
 
 
 2. Run localization, here we take Livox AVIA as an example:
@@ -107,9 +107,14 @@ Note that, during the initialization stage, it's better to keep the robot still.
 
 ## Related Works
 1. [FAST-LIO](https://github.com/hku-mars/FAST_LIO): A computationally efficient and robust LiDAR-inertial odometry (LIO) package
-2. [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.
-3. [LIO-SAM_based_relocalization](https://github.com/Gaochao-hit/LIO-SAM_based_relocalization): A simple system that can relocalize a robot on a built map based on LIO-SAM.
+2. [ikd-Tree](https://github.com/hku-mars/ikd-Tree): A state-of-art dynamic KD-Tree for 3D kNN search.
+3. [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.
+4. [LIO-SAM_based_relocalization](https://github.com/Gaochao-hit/LIO-SAM_based_relocalization): A simple system that can relocalize a robot on a built map based on LIO-SAM.
 
 
 ## Acknowledgments
 Thanks for the authors of [FAST-LIO](https://github.com/hku-mars/FAST_LIO) and [LIO-SAM_based_relocalization](https://github.com/Gaochao-hit/LIO-SAM_based_relocalization).
+
+## TODO
+1. Go over the timestamp issue of the published odometry and tf;
+2. Updating...