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Using OpenAI with ROS

Use the power of OpenAI combined with ROS simulations the easiest way

 

LEVEL Advanced  |   DURATION  24.5 hours   |   STUDENTS 897   | 

Course Overview

In this course, you are going to learn how to use the OpenAI ROS structure developed by The Construct and how to generate new code for it. The OpenAI ROS structure will allow you to develop for OpenAI with ROS in a much more easy way.

What You Will Learn

Basic Concepts of the OpenAI ROS structure

Set up the OpenAI ROS structure for a CartPole environment

Train the Cartpole with the QLearn algorithm

Set up the OpenAI ROS structure for a Moving Cube environment

Train the Cube with the QLlearn algorithm

Modifying the learning algorithm: DeepQ

Set up the OpenAI ROS structure for a Fetch Robot

Training Fetch robot with the HER algorithm from OpenAI baselines

You are going to program the following robots:

Fetch

Fetch

CartPole

CartPole

Moving Cube

Moving Cube

Hopper

Hopper

Learning Path
Unit 1

Introduction to the Course

A brief introduction to the Course contents. Includes a demo.
 (00:10 Hands on training)

Unit 2

Exploring the OpenAI ROS structure: CartPole

Learn how the OpenAI ROS structure is organized. Also, you will generate the whole structure for a CartPole environment.
(04:00 Hands on training)

Unit 3

Exploring the OpenAI ROS structure: Moving Cube #Part 1

Explore the OpenAI structure, using a RoboCube simulation. 
(00:10 Hands on training)

Unit 4

Exploring the OpenAI ROS structure with a Cube #Part 2

Generate the Robot Environment for training a Moving Cube.
(02:00 Hands on training)

Unit 5

Exploring the OpenAI Structure: RoboCube #Part 3

Explore the OpenAI structure, using a RoboCube simulation. Create the Task environment. 
(02:00 Hands on training)

Unit 6

Modifying the learning algorithm: Moving Cube with DeepQ from baselines

Learn how you can easily modify the learning script within the OpenAI ROS structure.
We will be using the deepQ algorithm from OpenAI baselines for training the Cube.
(02:00 Hands on training)

Unit 7

Modifying the learning algorithm: RoboCube

Learn how to modify the learning algorithm for the RoboCube environment. We will use the deepQ algorithm.
(02:00 Hands on training)

Unit 8

Exploring the OpenAI ROS structure with a Fetch robot

Generate the Robot Environment for training a Fetch robot.
(02:00 Hands on training)

Unit 9

Training the Fetch robot with HER algorithm from baselines

Generate the Task Environment for training a Fetch robot. 
(02:00 Hands on training)

Unit 10

Project: Training a Hopper robot

Apply all the concepts you have learned for training a Hopper robot. 
(08:00 Hands on training)

Unit 11

Final Recommendations

What to do after finishing the course
(00:10 Hands on training)

PRESENT

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