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World Congress 2022 • Jun 15, 2022

Enhancing AI-based Robotics with Simulation Workflows

Teresa Conceicao

How do you train autonomous robots for unpredictable, dangerous edge cases? Discover how simulated environments and synthetic data generation safely bridge the sim-to-real gap.

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#1 about 4 min

Transitioning from rigid machines to autonomous AI robots

How artificial intelligence addresses the limitations of pre-programmed machines by improving flexibility and environmental adaptation.

#2 about 3 min

Data and simulation requirements for AI robotics

Why parallel training and synthetic testing environments are critical for safely deploying reliable robotics logic.

#3 about 3 min

Introduction to Omniverse and Isaac Sim platforms

An overview of using digital twin development tools for creating photorealistic, physically accurate robotic simulations.

#4 about 4 min

Developing environments and importing external robot models

How to generate basic physics scenes, import URDF models, and configure robotic link articulations.

#5 about 2 min

Collaborating on robotic simulation environments across platforms

How integrating external design tools like Revit enables live, cross-team environment building for simulations.

#6 about 4 min

Programming robotic behavior with Python and OmniGraph

How developers define control logic using standalone scripts, user interface extensions, or visual graph programming nodes.

#7 about 2 min

Integrating the robotics operating system with Isaac Sim

How to operate external robotic brains while simulating the physical world and sensor perception in parallel.

#8 about 3 min

Generating synthetic training data to resolve labeling challenges

How simulation bypasses the cost, precision, and safety issues inherent in capturing complex real-world datasets.

#9 about 6 min

Bridging the sim-to-real gap using domain randomization tools

How tools like Isaac Replicator use physically based rendering and varied domains to create effective datasets for real models.

#10 about 4 min

Real-world production applications of Isaac Sim robotics

How industry partners leverage simulation for autonomous logistics, collaborative robot awareness, and wheeled locomotion policies.

#11 about 1 min

Procedural and handmade approaches for synthetic data generation

Why manual initial prototypes transition towards automated generation pipelines as machine learning workflows scale up.

Matching moments

2:11 min

Simulating physics and complex realities using emergent world models

Ankit Patel Ankit Patel +3 · WWC Europe 2026

2:23 min

Development roadmap for world models and physical robotics

Joerg Krall Joerg Krall · WWC Europe 2026

1:30 min

A three-computer paradigm for robotics development

Alexander Schwarz Alexander Schwarz · WWC 2025

2:55 min

Moving from AI software buzzwords to building actual robots

Iulia Feroli Iulia Feroli · WWC Europe 2026

2:22 min

Introduction to physical AI and the physical world

Moe Sani Moe Sani · WWC Europe 2026

1:20 min

Shifting focus from large language models to physical AI

Sergio Perez Sergio Perez · WWC Europe 2026

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