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.
Overview
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.
Learning Outcomes
โข Understanding of NVIDIA Isaac Sim and Omniverse robotics ecosystem
โข Ability to build robotics simulation environments using USD
โข Skills in sensor simulation and perception modeling
โข Knowledge of robot control and navigation workflows
โข Capability to design and test autonomous systems in simulation
Duration & Delivery Mode
21 hours
Target Audience
โข Robotics Engineers and Developers
โข AI/ML Engineers working on robotics perception
โข Automation and Control Engineers
โข Simulation and Digital Twin Engineers
โข Researchers in autonomous systems and robotics
โข Students in robotics, mechatronics, and AI
Pre-requisites
โข Basic understanding of robotics or automation concepts
โข Familiarity with Python programming is helpful
โข Basic knowledge of 3D simulation or CAD tools is an advantage
โข No prior Isaac Sim experience required
Skillset Achieved
โข Understanding NVIDIA Isaac Sim architecture within Omniverse
โข Building robotics simulation environments using USD
โข Sensor simulation (camera, LiDAR, IMU basics)
โข Robot movement and navigation simulation workflows
โข Introduction to ROS/ROS2 integration concepts
โข Physics-based simulation for robotics testing
โข Digital twin development for autonomous systems
Course Outcome
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.
Course Outline
Introduction to NVIDIA Isaac Sim and Omniverse Robotics Ecosystem
โข Overview of Isaac Sim platform and use cases
โข Robotics simulation vs real-world testing
โข Omniverse USD pipeline for robotics
โข Setting up Isaac Sim workspace
USD-Based Robotics Environment Setup
โข Creating and importing robot models
โข Scene hierarchy and environment structuring
โข Asset organization for robotics simulation
โข Basics of simulation-ready environments
Physics Engine and Simulation Fundamentals
โข Rigid body dynamics basics
โข Gravity, friction, and collision concepts
โข Simulation timestep and performance
โข Physics-based environment behavior
Hands-on exercises
Sensor Simulation and Perception Systems
โข Camera simulation for vision systems
โข Depth sensors and LiDAR concepts
โข Data output for robotics perception
โข Sensor noise and realism in simulation
Robot Control and Motion Simulation
โข Kinematics basics in simulation
โข Path planning concepts
โข Joint control and articulation systems
โข Navigation in simulated environments
Introduction to ROS/ROS2 Integration Concepts
โข Overview of ROS communication model
โข Isaac Sim and ROS bridge concepts
โข Data exchange between simulation and control systems
โข Workflow architecture for robotics pipelines
Hands-on exercises
Advanced Robotics Simulation Workflows
โข Multi-robot simulation environments
โข Scenario-based testing and validation
โข Edge cases and failure simulation
โข Performance tuning for large simulations
Autonomous Systems and Digital Twin Applications
โข Building robotics digital twins
โข Industrial automation use cases
โข Warehouse and logistics simulation
โข Smart robotics in manufacturing
Capstone Project: Robotics Simulation System
โข End-to-end robot environment setup
โข Sensor integration and navigation workflow
โข Simulation execution and validation
โข Final performance review
Hands-on exercises
Assessment Topics
โข Isaac Sim architecture and setup
โข USD-based robotics environments
โข Physics simulation fundamentals
โข Sensor modeling and perception systems
โข ROS/ROS2 integration concepts
โข Autonomous robotics simulation workflows
Evaluation
โข Robotics simulation setup exercises
โข Sensor modeling tasks
โข Motion planning and control assignments
โข Final Isaac Sim robotics project
Course Materials
Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.
Certification
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.
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WHO WILL BE FUNDING THE COURSE?
What Our Students Say
โThe training gave me a strong understanding of Isaac Sim and robotics workflows.โ
โExcellent structured approach to sensor simulation and robot control.โ
โThe course helped me build realistic robotics simulation environments.โ
โVery practical and relevant for modern robotics and digital twin systems.โ
โThis course is perfect for learning Isaac Sim from a real-world perspective.โ