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giskardpy

The core python library of the Giskard framework for constraint- and optimization-based robot motion control.

Installation instructions for 16.04/kinetic

Install the following python packages:

sudo pip install pybullet
sudo pip install scipy
sudo pip install casadi
sudo pip install sortedcontainers
sudo pip install hypothesis # only needed if you want to run tests
sudo pip install pandas

Now create the workspace

source /opt/ros/kinetic/setup.bash          # start using ROS kinetic
mkdir -p ~/giskardpy_ws/src                 # create directory for workspace
cd ~/giskardpy_ws                           # go to workspace directory
catkin init                                 # init workspace
cd src                                      # go to source directory of workspace
wstool init                                 # init rosinstall
wstool merge https://raw.githubusercontent.com/SemRoCo/giskardpy/constraint_update/rosinstall/catkin.rosinstall
                                            # update rosinstall file
wstool update                               # pull source repositories
rosdep install --ignore-src --from-paths .  # install dependencies available through apt
cd ..                                       # go to workspace directory
catkin build                                # build packages
source ~/giskardpy_ws/devel/setup.bash      # source new overlay

(optional) symengine

If you want to use the symengine backend, it can be install like this (does not have to be part of the ros workspace):

sudo apt-get install llvm-6.0-dev # or llvm-8-dev if you are using 18.04
git clone https://github.com/symengine/symengine.git
git clone https://github.com/symengine/symengine.py.git
cd symengine
git checkout `cat ../symengine.py/symengine_version.txt`
mkdir build
cd build
cmake -DWITH_LLVM:BOOL=ON -DBUILD_TESTS:BOOL=OFF -DBUILD_BENCHMARKS:BOOL=OFF ..
make
sudo make install
cd ../../symengine.py
sudo python setup.py install

Tutorials

http://giskard.de/wiki:tutorials

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The core python library of the Giskard framework for constraint- and optimization-based robot motion control.

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