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David von Wrangel
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added docker files
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‎README.md‎

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## Running locally
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### Installing Dependencies
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This code depends on [Drake](https://drake.mit.edu), specifically its Python bindings. To install Drake bindings follow the instruction on [Drake's Installation Page](https://drake.mit.edu/installation.html). Any of the installation methods listed should work. You can check that the installation was sucessful by following the instruction [here](https://drake.mit.edu/python_bindings.html#using-the-python-bindings).
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### Option 1: Docker
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We provide a [dockerfile](docker/deepnote/Dockerfile) with a custom build of [Drake](https://drake.mit.edu) that entails sampling based planners for the comparison. Note that the docker does not include a build of Gurobi, which has been only used in the Iris region generation.
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We have used Mosek to solve most of the examples. To solve using Mosek, you'll need to give Drake access to a Mosek license file as described [here](https://drake.mit.edu/bazel.html#mosek). Mosek provides a personal academic license for free.
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You will also need to install `gcs` and its dependencies. You can do this by running
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Pull the docker:
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```sh
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docker pull wrangelvid/drake:gcs-science-robotics
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```
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pip install -r requirements.txt
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Run the docker:
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```sh
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docker run -i -p 7000:7000 -p 8888:8888 -w /gcs-science-robotics -t wrangelvid/drake:gcs-science-robotics
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```
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### Running Examples
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Once all the dependencies have been installed, you can run the examples with jupyter notebooks which can be launched by calling
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In another shell, copy over your mosek license:
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```sh
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docker cp [PATH_TO_MOSEK.lic] [container_id]:/tmp/mosek.lic
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```
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jupyter-notebook
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Once the docker has been build and run, you can run the examples with jupyter notebooks:
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In the docker run the jupyter server:
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```sh
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jupyter notebook --ip 0.0.0.0 --no-browser --allow-root --NotebookApp.token=''
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```
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from inside this repository.
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### Running the Sampling Based Comparison
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If you want to compare GCS to sampling based planners (such as PRM), you'll need to install a custom fork of drake that includes bindings for sampling based planners. To do this run the following, including any of the proprietary solvers you have access to.
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On your machine go to http://localhost:8888/ You will find the reproduction notebooks in the reproduction folder.
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### Option 2: Local Installation
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If you want to compare GCS to sampling based planners (such as PRM), you'll need to install a custom fork of [Drake](https://drake.mit.edu) that includes bindings for sampling based planners. To do this run the following, including any of the proprietary solvers you have access to. You may build it with Gurobi.
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```
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git clone -b gcs_paper [email protected]:wrangelvid/drake.git
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git clone -b gcs-science-robotics [email protected]:wrangelvid/drake.git
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mkdir drake-build
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cd drake-build
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cmake -DWITH_MOSEK=ON [-DWITH_GUROBI=ON -DWITH_ROBOTLOCOMOTION_SNOPT=ON] ../drake
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cd drake-build
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export PYTHONPATH=${PWD}/install/lib/python3.9/site-packages:$PYTHONPATH
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```
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We have used Mosek to solve most of the examples. To solve using Mosek, you'll need to give Drake access to a Mosek license file as described [here](https://drake.mit.edu/bazel.html#mosek). Mosek provides a personal academic license for free.
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You will also need to install `gcs-science-robotics` and its dependencies. From inside this repository, run the following:
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```
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pip install -e .
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```
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Once all the dependencies have been installed, you can run the examples with jupyter notebooks which can be launched by calling
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```
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jupyter-notebook
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```
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from inside this repository.

‎docker/deepnote/Dockerfile‎

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# -*- mode: dockerfile -*-
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# vi: set ft=dockerfile :
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# git clone -b gcs-science-robotics [email protected]:wrangelvid/drake.git
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# mkdir drake-build
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# cd drake-build
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# cmake -DWITH_MOSEK=ON ../drake
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# make -j
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# Then copy this Dockerfile into the drake-build folder
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# docker build -f Dockerfile -t wrangelvid/drake:gcs-science-robotics ./install
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#
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# docker login
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# docker push wrangelvid/drake:gcs-science-robotics
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FROM ubuntu:jammy
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ARG DEBIAN_FRONTEND=noninteractive
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ENV SHELL /bin/bash
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# Open ports for meshcat:
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EXPOSE 7000-7099/tcp
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EXPOSE 8888/tcp
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LABEL org.opencontainers.image.authors="David von Wrangel"
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LABEL org.opencontainers.image.description="Drake with sampling based planning for the gcs paper"
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LABEL org.opencontainers.image.licenses="BSD-3-Clause"
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LABEL org.opencontainers.image.source="https://github.com/wrangelvid/drake/tree/gcs-science-robotics"
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LABEL org.opencontainers.image.vendor="Massachusetts Institute of Technology"
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ENV LANG en_US.UTF-8
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ENV LANGUAGE en_US.UTF-8
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ENV LC_ALL en_US.UTF-8
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ENV TZ=America/New_York
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RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone
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# Install curl and useful transport
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RUN apt-get update && yes "Y" \
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| apt-get install --no-install-recommends curl apt-transport-https
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RUN apt install -y tzdata
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COPY . /opt/drake/
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# Install drake prereqs.
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RUN apt-get update \
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&& yes "Y" | bash /opt/drake/share/drake/setup/install_prereqs
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RUN apt install python3-pip -y
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RUN apt install python-is-python3
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# Install deepnote dependencies.
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RUN apt-get update \
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&& yes "Y" | bash /opt/drake/share/drake/setup/deepnote/install_nginx
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RUN apt-get update \
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&& yes "Y" | bash /opt/drake/share/drake/setup/deepnote/install_xvfb
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RUN apt-get -q update && apt-get -q install -y --no-install-recommends git nginx-light xvfb && apt-get -q clean
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RUN pip3 install lxml matplotlib networkx numpy pandas pydot scipy
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RUN pip3 install -I ipywidgets
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RUN pip3 install jupyter_server
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RUN pip3 install --upgrade notebook
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# Install GCS repository.
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ENV DISPLAY=:1
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ENV MOSEKLM_LICENSE_FILE="/tmp/mosek.lic"
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RUN git clone https://github.com/RobotLocomotion/gcs-science-robotics.git
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ENV PYTHONPATH=/gcs-science-robotics:${PYTHONPATH}
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# Source environment of Drake installed to /drake
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ENV PYTHONPATH=/opt/drake/lib/python3.10/site-packages:${PYTHONPATH}

‎requirements.txt‎

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‎setup.py‎

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setup(
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name='gcs',
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version='0.1.0',
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packages=find_packages()
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packages=find_packages(),
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install_requires=[
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'lxml',
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'matplotlib',
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'networkx',
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'notebook',
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'numpy',
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'pandas',
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'pydot',
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'scipy',
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]
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)

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