DM-ACME compatible implementation of the Arm26 environment from Mujoco

Overview

ACME-compatible implementation of Arm26 from Mujoco

This repository contains a customized implementation of Mujoco's Arm26 model, that can be used with DeepMind's ACME framework to train a Reinforcement Learning agent. This is a more biologically realistic and more challenging effector to train than the typical reacher environment included in the original package.

This code is provided as-is, but feel free to log any issue if you find one. Any contribution is greatly appreciated!

Dependencies

The model relies on dm_control , as well as any dependencies dm_control may have, most notably a working Mujoco installation.

Usage

Import to your code via a normal import command import arm26. Make sure arm26.xml and arm26.py are in the same folder.

You can create the enviroment by calling

import arm26

environment = arm26.load(task_name)

The syntax is the same as for dm_control.suite.load, with the first argument (domain_name) being omitted.

Rendering

Below are examples showing that each of the six muscles work properly.

Shoulder extensor

GIF

Shoulder flexor

GIF

Elbow extensor

GIF

Elbow flexor

GIF

Bi-articular extensor

GIF

Bi-articular flexor

GIF

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