Giskard is an open source motion planning framework for ROS, which uses constraint and optimization based task space control to generate trajectories for the whole body of mobile manipulators.
source /opt/ros/noetic/setup.bash # source ROS
mkdir -p ~/giskardpy_ws/src # create directory for workspace
cd ~/giskardpy_ws # go to workspace directory
catkin init # init workspace, you might have to pip install catkin-tools
cd src # go to source directory of workspace
wstool init # init rosinstall
wstool merge https://raw.githubusercontent.com/SUTURO/giskardpy/master/rosinstall/noetic.rosinstall
# update rosinstall file
wstool update # pull source repositories
rosdep install --ignore-src --from-paths . # install dependencies available through apt
pip3 install -r giskardpy/requirements.txt # install python deps
cd .. # go to workspace directory
catkin build # build packages
source ~/giskardpy_ws/devel/setup.bash # source new overlay
Giskard uses Adrian Röfer's bullet bindings instead of the official ones, as they are much faster for our use case. Install them like this:
mkdir -p ~/libs && cd ~/libs # choose a place where you want to build pybullet
git clone https://github.com/SemRoCo/bullet3.git
cd bullet3 # be sure to be in the bullet3 folder
./build_better_pybullet.sh # this script will also clone and build pybind11 into libs
source ~/.bashrc # the script adds a python path modification to your bashrc
To test your installation do:
$ python3
Python 3.8.10 (default, Nov 14 2022, 12:59:47)
[GCC 9.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import betterpybullet
>>>
If it doesn't work, make sure that your $PYTHONPATH includes something like
/path/to/your/bullet3/build_cmake/better_python:/path/to/your/bullet3/examples/pybullet.
Giskard supports multiple QP solvers and will automatically use the fasted installed solver.
qpalm: Default solver, because it is the easiest to install and still reasonably fast.qpSWIFT: Fastest open source solver in most cases. Install instructions: https://github.com/qpSWIFT/qpSWIFT.gurobi: Commercial solver. Slightly slower thanqpSWIFTon most robots. OutperformsqpSWFITon systems with a lot of dof and/or a large prediction horizon.sudo pip3 install gurobipy- You can apply for a free academic license or buy one here: https://www.gurobi.com/academia/academic-program-and-licenses/
- If you have vpn access to or are in the local network of the IAI of the University of Bremen, follow these instructions: https://ai.uni-bremen.de/wiki/intern/adm/gurobi
https://github.com/SemRoCo/giskardpy/wiki
Stelter, Simon, Georg Bartels, and Michael Beetz. "An open-source motion planning framework for mobile manipulators using constraint-based task space control with linear MPC." 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2022.