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Bayesian Generalized Kernel Inference for Terrain Traversability Mapping

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Traversability Mapping and Motion Planning

This repository contains code for a traversability mapping and motion plannign system for ROS compatible UGVs. The system takes in point cloud from a Velodyne VLP-16 Lidar and outputs a traversability map for autonomous navigation in real-time. A demonstration of the system can be found here -> https://www.youtube.com/watch?v=4pdBpeRGXmw

Get Started

  • Install ROS.

  • Install LeGO-LOAM.

  • Install ROS Navigation stack. You can install it by running sudo apt-get install ros-indigo-navigation. If you are using other versions of ROS, replace indigo in the command with your ROS version.

Compile

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

cd ~/catkin_ws/src
git clone https://github.com/TixiaoShan/traversability_mapping.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.

Run the System (in simulation)

  1. Run the launch file:
roslaunch traversability_mapping offline.launch
  1. Play existing bag files:
rosbag play *.bag --clock --topic /velodyne_points /imu/data

Notes: our system only needs /velodyne_points for input from bag files. However, a 3D SLAM method usually needs /imu/data.

Run the System (with real robot)

Run the launch file:

roslaunch traversability_mapping online.launch

Cite Traversability_Mapping

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

@inproceedings{bayesian2018shan,
  title={Bayesian Generalized Kernel Inference for Terrain Traversability Mapping},
  author={Shan, Tixiao and Wang, Jinkun and Englot, Brendan and Doherty, Kevin},
  booktitle={In Proceedings of the 2nd Annual Conference on Robot Learning},
  year={2018}
}

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