Giskard examples

Giskard examples in Jupyter notebooks

Quick Start

Option 1: Test Image Locally (Under repo directory)

• Run Docker image with X-forwarding

  xhost +local:docker && \
  docker compose -f ./binder/docker-compose.yml up  --build && \
  xhost -local:docker

• Open Web browser and go to http://localhost:8888/lab/tree/giskard_examples/notebooks/playground.ipynb

• To stop and remove container:

  docker compose -f ./binder/docker-compose.yml down

Option 2: Run on BinderHub

https://binder.intel4coro.de/v2/gh/yxzhan/giskard-examples.git/mujoco_actions_devel?urlpath=%2Flab%2Ftree%2Fnotebooks%2Fplayground.ipynb

Tutorials of giskardpy

https://github.com/SemRoCo/giskardpy/wiki

Publications

S. Stelter, G. Bartels and M. 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), Kyoto, Japan, 2022, pp. 1671-1678, doi: 10.1109/IROS47612.2022.9982245.

jknowrob

A Jupyter Kernel for KnowRob.

Inspired by ayceesrk/jupyter-swi-prolog

Prerequisite

1. Jupyter notebook installed on your system pip install jupyter

Supported environments

Only python3 is supported

Installation

1. Install SWI-Prolog.
2. Install jknowrob pip install git+https://github.com/sasjonge/jupyter-knowrob.git
3. Change directory to your jupyters kernel directory. Typically ~/.local/share/jupyter/kernels.
4. mkdir jknowrob && cd jknowrob
5. Install kernel spec: wget https://raw.githubusercontent.com/sasjonge/jupyter-knowrob/master/kernel.json
6. Restart jupyter: jupyter notebook
7. Profit