Transferring Robot Learning Policies From Simulation to Reality

Welcome to our course on Transferring Robot Learning Policies from Simulation to Reality, which we often refer to as sim-to-real.

While this course won’t focus specifically on Isaac Lab, the principles we’ll cover are important to understand before you start developing robot learning policies in Isaac Lab. Our goal in this course is to teach you about sim-to-real, including best practices and pitfalls to avoid.

Learning Objectives

By the end of this course you’ll be able to:

• Understand the challenges of reinforcement learning in robotics.

• Explain the concept of the “reality gap” and its characteristics.

• Describe various techniques for bridging the reality gap.

• Evaluate strategies for leveraging privileged information in robot learning.

• Implement best practices for successful sim-to-real transfer in robotics applications.

Note

This module does not contain hands-on activities.