global-LeGO-LOAM

It contains LeGO-LOAM mapping algorithm and Particle filter localization algorithm. To find robot pose, map should be built first by LeGO-LOAM. For computation efficiency, all nodes are implemented as nodelet.

Preparation

cd src && git clone https://github.com/haeyeoni/global-LeGO-LOAM
cd .. && catkin_make

Build map (Using KITTI dataset)

(0) Download KITTI dataset and make as bag file format (Reference lik)

(1) Mapping

roslaunch lego_loam kitti_mapping.launch
(new terminal) rosbag play kitti.bag --clock

In the launch file, you can set map and key pose path. Model is for generating descriptors and is used for finding initial pose of Monte Carlo Localization.

• Result map

(2) Localization

roslaunch lego_loam kitti_localization.launch
(new terminal) rosbag play kitti.bag --clock

The argument paths (model_path, feature_cloud_path, key_pose_path, map_save_path) should be set same as the mapping.

• Result