A-LOAM is an Advanced implementation of LOAM (J. Zhang and S. Singh. LOAM: Lidar Odometry and Mapping in Real-time), which uses Eigen and Ceres Solver to simplify code structure. This code is modified from LOAM and LOAM_NOTED. This code is clean and simple without complicated mathematical derivation and redundant operations. It is a good learning material for SLAM beginners.
Modifier: Tong Qin, Shaozu Cao
Ubuntu 64-bit 16.04 or 18.04. ROS Kinetic or Melodic. ROS Installation
Follow Ceres Installation.
Follow PCL Installation.
Clone the repository and catkin_make:
cd ~/catkin_ws/src
git clone https://github.com/HKUST-Aerial-Robotics/A-LOAM.git
cd ../
catkin_make
source ~/catkin_ws/devel/setup.bash
Download NSH indoor outdoor to YOUR_DATASET_FOLDER.
roslaunch aloam_velodyne aloam_velodyne_16.launch
rosbag play YOUR_DATASET_FOLDER/nsh_indoor_outdoor.bag
Download KITTI Odometry dataset to YOUR_DATASET_FOLDER and set the dataset_folder and sequence_number parameters in kitti_helper.launch file. Note you also convert KITTI dataset to bag file for easy use by setting proper parameters in kitti_helper.launch.
roslaunch aloam_velodyne aloam_velodyne_64.launch
roslaunch aloam_velodyne kitti_helper.launch
To further facilitate the building process, we add docker in our code. Docker environment is like a sandbox, thus makes our code environment-independent. To run with docker, first make sure ros and docker are installed on your machine. Then add your account to docker group by sudo usermod -aG docker $YOUR_USER_NAME. Relaunch the terminal, type:
cd ~/catkin_ws/src/A-LOAM/docker
make build
The build process may take a while depends on your machine. After that, run ./run.sh 16 or ./run.sh 64 to launch A-LOAM, then you should be able to see the result.
Thanks for LOAM(J. Zhang and S. Singh. LOAM: Lidar Odometry and Mapping in Real-time) and LOAM_NOTED.