LeGO-LOAM for kitti dataset

This repository contains the modified code of LeGO-LOAM to run and evaluate with the kitti-data set. When you run the code, you'll get the trajectory results of LeGO-LOAM in KITTI ground-truth format and you can directly evaluate the result with KITTI ground-truth by EVO-eval kit. Wish you find it helpful, especially for those who are not familiar with ROS and LOAM.

Dependency

• ROS (tested with indigo and kinetic)
• gtsam (Georgia Tech Smoothing and Mapping library, 4.0.0-alpha2)

 wget -O ~/Downloads/gtsam.zip https://github.com/borglab/gtsam/archive/4.0.0-alpha2.zip
 cd ~/Downloads/ && unzip gtsam.zip -d ~/Downloads/
 cd ~/Downloads/gtsam-4.0.0-alpha2/
 mkdir build && cd build
 cmake ..
 sudo make install

Compile

1. You can use the following commands to download and compile the package.

cd ~/catkin_ws/src
git clone https://github.com/Mitchell-Lee-93/kitti-lego-loam.git
cd ..
rosdep install --from-paths src --ignore-src -r -y
catkin_make

Making new bagfile from kitti dataset

Download odometry dataset(color or gray, velodyne, calibration, ground truth) from : http://www.cvlibs.net/datasets/kitti/eval_odometry.php and Merge them all in one dataset directory

1. Edit the launch file

gedit ~/catkin_ws/src/kittibag/launch/kittibag.launch

Change 'dataset_folder' and 'output_bag_file' to your own directories

2. Run the launch file:

roslaunch kittibag kittibag.launch

Run the package

1. Before run, you should change the directory of the result files

gedit ~/catkin_ws/src/LeGO-LOAM/LeGO-LOAM/launch/run.launch

change 'RESULT_PATH' to your result dir

2. Run the launch file:

roslaunch lego_loam run.launch

Notes: The parameter "/use_sim_time" is set to "true" for simulation, "false" to real robot usage.

3. Play existing bag files:

rosbag play *.bag --clock 

Evaluation with evo kit

Check and follow this repository

https://github.com/MichaelGrupp/evo

Evaluation results

For A-LOAM with kitti

check https://github.com/Mitchell-Lee-93/kitti-A-LOAM

Original code from

https://github.com/RobustFieldAutonomyLab/LeGO-LOAM

Modified code

1. utility.h

for Velodyne 64 channel

extern const string pointCloudTopic = "/kitti/velo/pointcloud"; <- you should check your own bag file topic

//param for vel-64
extern const int N_SCAN = 64;
extern const int Horizon_SCAN = 1800;
extern const float ang_res_x = 0.2;
extern const float ang_res_y = 0.427;
extern const float ang_bottom = 24.9;
extern const int groundScanInd = 50;

2. featureAssociation.cpp

Since kitti data already have removed the distortion

float s 10 * (pi->intensity - int(pi->intensity)); -> float s = 1;

// to delete all the code that corrects point cloud distortion
TransformToEnd(&cornerPointsLessSharp->points[i], &cornerPointsLessSharp->points[i]); -> removed
TransformToEnd(&surfPointsLessFlat->points[i], &surfPointsLessFlat->points[i]); -> removed

*Notes: The parameter "loopClosureEnableFlag" is set to "true" for SLAM. 

3. transformfusion.cpp

To correct two diffrent TF of lego-loam results and kitti gt. And also to save the results in kitti gt format

From line 222 to 286, saving results code added

Reference : RobustFieldAutonomyLab/LeGO-LOAM#12