Using OpenAI with ROS Course - Python
Use the power of OpenAI combined with ROS simulations the easiest way.
Course Summary
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 qlearn 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
Course Overview
Introduction to the Course
Unit for previewing the contents of the Course.
Exploring the OpenAI Structure: CartPole
Follow, step by step, the full workflow of a CartPole simulated environment, including all the environments and scripts involved in its training.
Exploring the OpenAI Structure: RoboCube. Part 1
Learn how to apply the openai_ros package to your own robot.
Exploring the OpenAI Structure: RoboCube. Part 2
Learn how to create a Robot Environment for a Moving Cube with a single disk in the roll axis using the OpenAI ROS structure.
Exploring the OpenAI Structure: RoboCube. Part 3
Learn how to define the learning task of your robot by creating a Task Environment for a Moving Cube with a single disk in the roll axis. Also, you will use the Qlearn algorithm for training the RoboCube.
Save and Load the Learned Policy
Learn how to save the learned policy and how to load it to apply what the agent has learned.
Modifying the learning algorithm: CartPole
Learn how to set up the environment in order to be able to use the OpenAI Baselines deepq algorithm.
Modifying the learning algorithm: RoboCube
Learn how to set up the environment in order to be able to use the OpenAI Baselines deepq algorithm.
Training a Fetch Robot. Part 1
A step-by-step look at how to build the Robot Environment for training a Fetch robot.
Training a Fetch Robot. Part 2
A step-by-step look at how to build the Task Environment for training a Fetch robot.
Project: Training a Hopper robot
Create all the environments needed in order to be able to train the Hopper robot.
Teachers
Ricardo Tellez
Dreaming of a world where robots actually understand what they are doing. Developing the definitive tool that will make it happen.
Miguel Angel Rodriguez
Crashing engineering problems. Building solutions.
Alberto Ezquerro
Making easier the way the people learn how to program robots.
Robots used
CartPole Sim robot
Cube Sim robot
Fetch robot
Hopper robot
Learning Path
Machine Learning for Robots