LeGO-LOAM

This repository contains code for a lightweight and ground optimized lidar odometry and mapping (LeGO-LOAM) system for ROS compatible UGVs. The system takes in point cloud from a Velodyne VLP-16 Lidar (palced horizontal) and optional IMU data as inputs. It outputs 6D pose estimation in real-time. A demonstration of the system can be found here -> https://www.youtube.com/watch?v=O3tz_ftHV48

Dependency

ROS (tested with indigo and kinetic)
gtsam (Georgia Tech Smoothing and Mapping library)

Compile

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

cd ~/catkin_ws/src
git clone https://github.com/RobustFieldAutonomyLab/LeGO-LOAM.git
cd ..
catkin_make -j1

When you compile the code for the first time, you need to add "-j1" behind "catkin_make" for generating some message types. "-j1" is not needed for future compiling.

The system

LeGO-LOAM is speficifally optimized for a horizontally placed VLP-16 on a ground vehicle. It assumes there is always a ground plane in the scan. The UGV we are using is Clearpath Jackal. It has a built-in IMU.

The package performs segmentation before feature extraction.

Lidar odometry performs two-step Levenberg Marquardt optimization to get 6D transformation.

New sensor

The key thing to adapt the code to a new sensor is making sure the point cloud can be properly projected to an range image and ground can be correctly detected. For example, VLP-16 has a angular resolution of 0.2° and 2° along two directions. It has 16 beams. The angle of the bottom beam is -15°. Thus, the parameters in "utility.h" are listed as below. When you implement new sensor, make sure that the ground_cloud has enough points for matching.

extern const int N_SCAN = 16;
extern const int Horizon_SCAN = 1800;
extern const float ang_res_x = 0.2;
extern const float ang_res_y = 2.0;
extern const float ang_bottom = 15.0;
extern const int groundScanInd = 7;

Run the package

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.

Play existing bag files:

rosbag play *.bag --clock --topic /velodyne_points /imu/data

Notes: Though /imu/data is optinal, it can improve estimation accuracy greatly if provided. Some sample bags can be downloaded from here If your IMU frame doesn't align with Velodyne frame, use of IMU data will cause significant drift.

Cite LeGO-LOAM

Thank you for citing our LeGO-LOAM paper if you use any of this code:

@inproceedings{legoloam2018,
  title={LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain},
  author={Tixiao Shan and Brendan Englot},
  booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages={Accepted, To Appear in October},
  year={2018},
  organization={IEEE}
}