PyRoboLearn

This repository contains the code for the PyRoboLearn (PRL) framework: a Python framework for Robot Learning. This framework revolves mainly around 7 axes: simulators, worlds, robots, interfaces, learning tasks (= environment and policy), learning models, and learning algorithms.

Requirements

The framework has been tested with Python 2.7 and Ubuntu 16.04 and 18.04. We plan to migrate soon to Python 3.5.

Installation

1. First download the pip Python package manager and create a virtual environment for Python 2.7 as described in the following link: https://packaging.python.org/guides/installing-using-pip-and-virtualenv/ On Ubuntu, in the terminal, you can type to download and install pip and virtualenv:

sudo apt install python-pip
sudo pip install virtualenv

You can then create the virtual environment by typing:

virtualenv -p /usr/bin/python2.7 <virtualenv_name>
# activate the virtual environment
source <virtualenv_name>/bin/activate

where <virtualenv_name> is a name of your choice for the virtual environment. For instance, it can be py2.7.

To deactivate the virtual environment, just type:

deactivate

2. clone this repository and install the requirements and the setup.py

git clone https://github.com/robotlearn/pyrobolearn
cd pyrobolearn
pip install numpy cython
pip install http://github.com/cornellius-gp/gpytorch/archive/alpha.zip
pip install -e .  # this will install pyrobolearn as well as all the required packages (so no need for: pip install -r requirements.txt)

How to use it?

Check the README.md file in the examples folder.

Citation

@misc{delhaisse2019pyrobolearn,
    author = {Delhaisse, Brian and Rozo, Leonel, and Caldwell, Darwin},
    title = {PyRoboLearn: A Python Framework for Robot Learning Practitioners},
    howpublished = {\url{https://github.com/robotlearn/pyrobolearn}},
    year=2019,
}