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.
sudo pip3 install scipy casadi sortedcontainers hypothesis pandas numpy trimesh colour pycollada
sudo apt install python3-dev
This step is optional but recommanded because Gurobi is significantly faster than QPOases, but it requires a license. If Gurobi is not installed, Giskard will use QPOases automatically as a backup.
sudo pip3 install gurobipy- If you have vpn access 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
- Otherwise you can apply for a free academic license or buy one here: https://www.gurobi.com/academia/academic-program-and-licenses/
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/SemRoCo/giskardpy/devel/rosinstall/noetic.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
Giskard uses Adrian Röfer's bullet bindings instead of the official ones, as they are much faster for our use case.
./scripts/build_better_pybullet.sh /path/of/your/choosing
source ~/.bashrc
Where /path/of/your/choosing can be e.g. a new folder in your home directory.
If everything worked fine, you should be able to do:
import betterpybullet as bpb