UR3-Deep-Reinforcement-Learning

You will be able to learn various tasks of the UR3 with robotiq85 gripper robot.
Learning method is based on the DRL(Deep Reinforcement Learning).
In this repo, we use CoppeliaSim (previously called V-REP), Pyrep.
Tasks

• DRL framework : rllib

• Supported tasks

  Tasks	Learned Task Example	Learning Curve
  reach
  TO DO	-	-

Install

This repo was tested with Python 3.7.9 version.

Coppeliasim

PyRep requires version 4.1(other versions may have bugs) of CoppeliaSim. Download:

• Ubuntu 16.04
• Ubuntu 18.04
• Ubuntu 20.04

Add the following to your ~/.bashrc file: (NOTE: the 'EDIT ME' in the first line)

export COPPELIASIM_ROOT=EDIT/ME/PATH/TO/COPPELIASIM/INSTALL/DIR
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$COPPELIASIM_ROOT
export QT_QPA_PLATFORM_PLUGIN_PATH=$COPPELIASIM_ROOT

PyRep

Once you have downloaded and set CoppeliaSim, you can install PyRep: Move to home workspace

git clone https://github.com/stepjam/PyRep.git
cd PyRep
pip install -r requirements.txt
pip install -e .

Remember to source your bashrc (source ~/.bashrc) or zshrc (source ~/.zshrc) after this.

LearnToMoveUR3

Move to home workspace Clone repo and Install the python library:

git clone https://github.com/isk03276/LearnToMoveUR3.git
cd LearnToMoveUR3
pip install -r requirements.txt

Getting Started

python main.py --env-id ENV_ID --load-from MODEL_CHECKPOINT_PATH #Train
python main.py --env-id reach --test --load-from MODEL_CHECKPOINT_PATH #Test

Use Pretrained Model

python main.py --env-id reach --load-from pretrained_models/reach --test