NVIDIA Omniverse (Isaac Sim) Training is an advanced, hands-on program designed to equip learners with the skills required to develop, simulate, and validate robotics systems using NVIDIA Isaac Sim within the Omniverse ecosystem. This training focuses on robotics simulation workflows, sensor modeling, physics-based simulation, ROS integration concepts, USD-based environments, and digital twin development for autonomous systems. Participants will gain practical experience in building realistic robotic environments for testing perception, navigation, manipulation, and automation scenarios.

• Understanding of NVIDIA Isaac Sim and Omniverse robotics ecosystem
• Ability to build robotics simulation environments using USD
• Skills in sensor simulation and perception modeling
• Knowledge of robot control and navigation workflows
• Capability to design and test autonomous systems in simulation

• Robotics Engineers and Developers
• AI/ML Engineers working on robotics perception
• Automation and Control Engineers
• Simulation and Digital Twin Engineers
• Researchers in autonomous systems and robotics
• Students in robotics, mechatronics, and AI

• Basic understanding of robotics or automation concepts
• Familiarity with Python programming is helpful
• Basic knowledge of 3D simulation or CAD tools is an advantage
• No prior Isaac Sim experience required

• Understanding NVIDIA Isaac Sim architecture within Omniverse
• Building robotics simulation environments using USD
• Sensor simulation (camera, LiDAR, IMU basics)
• Robot movement and navigation simulation workflows
• Introduction to ROS/ROS2 integration concepts
• Physics-based simulation for robotics testing
• Digital twin development for autonomous systems

Upon completion of this training, participants will be able to build and simulate robotics systems using NVIDIA Isaac Sim. They will be capable of creating physics-based robotic environments, simulating sensors, and validating autonomous system behavior in virtual digital twin setups.

Introduction to NVIDIA Isaac Sim and Omniverse Robotics Ecosystem
• Overview of Isaac Sim platform and use cases
• Robotics simulation vs real-world testing
• Omniverse USD pipeline for robotics
• Setting up Isaac Sim workspace

USD-Based Robotics Environment Setup
• Creating and importing robot models
• Scene hierarchy and environment structuring
• Asset organization for robotics simulation
• Basics of simulation-ready environments

Physics Engine and Simulation Fundamentals
• Rigid body dynamics basics
• Gravity, friction, and collision concepts
• Simulation timestep and performance
• Physics-based environment behavior

Hands-on exercises

Sensor Simulation and Perception Systems
• Camera simulation for vision systems
• Depth sensors and LiDAR concepts
• Data output for robotics perception
• Sensor noise and realism in simulation

Robot Control and Motion Simulation
• Kinematics basics in simulation
• Path planning concepts
• Joint control and articulation systems
• Navigation in simulated environments

Introduction to ROS/ROS2 Integration Concepts
• Overview of ROS communication model
• Isaac Sim and ROS bridge concepts
• Data exchange between simulation and control systems
• Workflow architecture for robotics pipelines

Hands-on exercises

Advanced Robotics Simulation Workflows
• Multi-robot simulation environments
• Scenario-based testing and validation
• Edge cases and failure simulation
• Performance tuning for large simulations

Autonomous Systems and Digital Twin Applications
• Building robotics digital twins
• Industrial automation use cases
• Warehouse and logistics simulation
• Smart robotics in manufacturing

Capstone Project: Robotics Simulation System
• End-to-end robot environment setup
• Sensor integration and navigation workflow
• Simulation execution and validation
• Final performance review

Hands-on exercises

• Isaac Sim architecture and setup
• USD-based robotics environments
• Physics simulation fundamentals
• Sensor modeling and perception systems
• ROS/ROS2 integration concepts
• Autonomous robotics simulation workflows

• Robotics simulation setup exercises
• Sensor modeling tasks
• Motion planning and control assignments
• Final Isaac Sim robotics project

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Participants who successfully complete the training will receive an AcadNXT Certification in NVIDIA Omniverse (Isaac Sim) Training, validating their expertise in robotics simulation, digital twin development, and autonomous system testing using Isaac Sim.