This library is an implementation of GPMP2 (Gaussian Process Motion Planner 2) algorithm described in Motion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs (RSS 2016). The core library is developed in C++ language, and an optional Matlab toolbox is provided. Examples are provided in Matlab scripts. A ROS interface is also available within PIPER.
- CMake >= 2.6 (Ubuntu:
sudo apt-get install cmake), compilation configuration tool. - Boost >= 1.50 (Ubuntu:
sudo apt-get install libboost-all-dev), portable C++ source libraries. - GTSAM >= 4.0 alpha, a C++ library that implement smoothing and mapping (SAM) framework in robotics and vision. Here we use factor graph implementations and inference/optimization tools provided by GTSAM.
In the library folder execute:
$ mkdir build
$ cd build
$ cmake ..
$ make check # optional, run unit tests
$ make install
An optional Matlab toolbox is provided to use our library in Matlab. To enable Matlab toolbox during compilation:
$ cmake -DGPMP2_BUILD_MATLAB_TOOLBOX:OPTION=ON -DGTSAM_TOOLBOX_INSTALL_PATH:PATH=/path/install/toolbox ..
$ make install
After you install the Matlab toolbox, don't forget to add /path/install/toolbox to your Matlab path.
The GaussianProcessMotionPlanner library is designed to be cross-platform. It has been tested on Ubuntu Linux and Windows for now.
- Ubuntu: GCC 4.8 - 4.9, 5.3 - 5.4
- Windows: Visual C++ 2015 (Matlab toolbox not tested)
- Boost: 1.50 - 1.61
Please use Github issue tracker to report bugs. For other questions please contact Sourangshu Ghosh
GaussianProcessMotionPlanner is released under the MIT license, reproduced in the file LICENSE in this directory.