Streamlining the transfer of simulated robot learning to the real-world.

Table of Contents

• What is EAGERx
• Installation
  • Extras: GUI
  • Extras: training visualization
• Tutorials
• Dependencies
  • ROS
• Cite EAGERx
• Maintainers
• How to contact us
• Acknowledgements

What is EAGERx

EAGERx (Engine Agnostic Gym Environments for Robotics) enables users to easily define new tasks, switch from one sensor to another, and switch from simulation to reality with a single line of code by being invariant to the physics engine. EAGERx explicitly addresses the differences in learning between simulation and reality, with essential features for roboticists such as a safety layer, signal delay simulation, and controller switching for resets. A single RL pipeline that works with both the simulated and real robots eliminates the chance for mismatches between the simulation and reality implementation. The defined task follows the OpenAI Gym interface, so one can plug in algorithms from established RL libraries (e.g., Stable-baselines3 ) to solve the task afterward, again minimizing implementation errors.

Full documentation and tutorials available here.

Installation

You can do a minimal installation of EAGERx with:

pip3 install eagerx

Note

EAGERx depends on a minimal ROS installation. Fortunately, you can use eagerx anywhere as you would any python package, so it does not impose a ROS package structure on your project. See here for installation instructions.

Extras: GUI

To install the whole set of features, you will need additional packages. You can install everything by running:

pip3 install eagerx-gui

The construction of an environment via the GUI.

Extras: training visualization

In robotics it is crucial to monitor the robot's behavior during the learning process. Luckily, inter-node communication within EAGERx can always be listened to externally, so that any relevant information stream can be trivially monitored on-demand (e.g. with rqt_plot).

Note

rqt_plot is included in the desktop or desktop-full ROS installation. See here for installation instructions.

Tutorials

A number of tutorials are available in the form of Google Colabs:

• Tutorial 1: Environment Creation and Training with EAGERx
• Tutorial 2: Reset and Step Function
• Tutorial 3: Converters
• Tutorial 4: Nodes and Graph Validity

For more information see the docs or the eagerx_tutorials package.

Dependencies

Below you find instructions for installing dependencies required for EAGERx.

ROS

See the ROS Installation Options, or do the following. By replacing <DISTRO> with the supported ROS distributions (noetic, melodic), and <PACKAGE> with the installation type (ros-base, desktop, desktop-full), a minimal ros installation can be installed with:

sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
sudo apt install curl # if you haven't already installed curl
curl -s https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc | sudo apt-key add -
sudo apt update
sudo apt install ros-<DISTRO>-<PACKAGE>
sudo apt-get install ros-<DISTRO>-cv-bridge

Make sure to source /opt/ros/<DISTRO>/setup.bash in the environment where you intend to eagerx in. It can be convenient to automatically source this script every time a new shell is launched. These commands will do that for you if you:

echo "source /opt/ros/<DISTRO>/setup.bash" >> ~/.bashrc
source ~/.bashrc

In case you make use of a virtual environment, move to the directory containing the .venv and add source /opt/ros/<DISTRO>/setup.bash to the activation script before activating the environment with this line:

echo "source /opt/ros/<DISTRO>/setup.bash" >> .venv/bin/activate

Cite EAGERx

If you are using EAGERx for your scientific publications, please cite:

@article{eagerx,
    author  = {van der Heijden, Bas and Luijkx, Jelle, and Ferranti, Laura and Kober, Jens and Babuska, Robert},
    title = {EAGERx: Engine Agnostic Gym Environment for Robotics},
    year = {2022},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/eager-dev/eagerx}}
}

Maintainers

EAGERx is currently maintained by Bas van der Heijden (@bheijden) and Jelle Luijkx (@jelledouwe).

How to contact us

Follow us on Twitter @EagerxD!

For any question, send an e-mail to [email protected].

Acknowledgements

EAGERx is funded by the OpenDR Horizon 2020 project.