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Getting Started With Isaac Lab
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Getting Started With Isaac Lab
Table of Contents
Contents
An Introduction to Robot Learning and Isaac Lab
Overview
What Is Robot Learning?
What Is Robot Learning?
Robot Learning Algorithms and Techniques
Supervised Learning
Unsupervised Learning
Imitation Learning
Reinforcement Learning
History of NVIDIA Robotics Simulators and Environments
NVIDIA Robotics Simulators and Environments
Isaac Gym Standalone
Isaac Sim
Isaac Lab
Data Flow Between Isaac Sim and Isaac Lab
Isaac Lab in Use
Available Robots
Available Robots
Available Sensors
Available Environments
Tiled Rendering
Review
Review
Tying It All Together
Train Your First Robot in Isaac Lab
Overview
Reinforcement Learning for Robots
How Isaac Lab Accelerates Reinforcement Learning
Task Design and the Markov Decision Process
Training the Cartpole
Get Started In Isaac Lab
Running the Training
Analyzing the Code
Running our Policy
Conclusion
Feedback
Train Your Second Robot in Isaac Lab
Overview
Isaac Lab Setup
Robot Configuration in Isaac Lab
Manager Configuration
Configuring the managers
Tying it all together
Custom Reward Functions
Evaluating the Results
Optional Challenges
Conclusion
Feedback
Transferring Robot Learning Policies From Simulation to Reality
Overview
The Successes of Reinforcement Learning
Reinforcement Learning
The Challenges of Reinforcement Learning
Simulation: A Game-Changer
What Is the Reality Gap?
The Reality Gap
Visualizing the Reality Gap
Bridging the Gap: Simulation Enhancement
Domain Randomization
Visual Domain Randomization
Depth Camera Randomization
Point Cloud Perturbations
Bridging the Gap: Real-World Data Integration
System Identification
Actuator Modeling
Digital Twins
Neural Rendering
World Models
Regularization
Regularization
Leveraging Privileged Information
Considerations When Bridging the Reality Gap
Considerations
Tips for Sim-to-Real
Review
Quiz
Index
