Deploying Policies from Isaac Lab to Isaac Sim

Описание: Add to your calendar: https://www.addevent.com/event/cA2626...

In this NVIDIA OpenUSD Insiders livestream featuring Sanjuna Mathews, developers will learn how to train a robot using reinforcement learning in Isaac Lab and export the resulting policy for deployment. The session will demonstrate the full deployment pipeline within Isaac Sim. Toward the end, there will be a brief walkthrough of how the deployed policy interfaces with ROS 2 topics for observation and action exchange providing a foundation for sim-to-real transfer.

Chapters:
00:00 Intro and Guest Welcome
2:07 News Announcements & Community Events
5:17 About the Guest: Sanjuna’s Background
7:00 Livestream Topic Overview
8:13 Reinforcement Learning Basics
9:50 Discussion: Observations & Sensors in RL
12:48 Demo Setup: Franka Robot & Microwave Task
14:44 Training the Policy in Isaac Lab
16:53 Managed vs. Direct Environments in Isaac Lab
22:18 Task Sequence: Reach, Align, Grasp, Open Door
23:36 Reward Functions and Learning Stages
28:58 Visualization & Headless Training
34:35 Exporting Policies & Deployment Workflow
42:51 Deployment Pipeline & Simulation in Isaac Sim
1:01:44 ROS2 Integration and Real Robot Deployment

About our livestreams:

Welcome to OpenUSD Insider—a livestream series that brings together developers, researchers, and industry leaders to explore the latest tools, workflows, and innovations shaping the future of OpenUSD. From digital twins and simulation to robotics and industrial applications, each episode features real-world use cases, technical deep dives, and insights from those working on the cutting edge.

Whether you're building complex systems, training autonomous robots, or streamlining simulation pipelines, this series is your front-row seat to the evolving OpenUSD ecosystem.

📆 Check out the full calendar for all of our upcoming events → https://nvda.ws/3JqaWnA

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