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Module 3: NVIDIA Isaac Sim

Overview​

Module 3 (Weeks 8-10) focuses on NVIDIA Isaac Sim, a high-fidelity simulation platform for developing and testing perception systems for autonomous robots.

Duration: 3 weeks (30 hours estimated) Weeks: 8-10 Prerequisites: Module 1 (ROS 2), Module 2 (Simulation), basic computer vision

Learning Objectives​

  1. Deploy Isaac Sim - Set up and configure NVIDIA Isaac Sim with ROS 2 integration
  2. Build Perception Pipelines - Implement camera and lidar-based perception systems
  3. Object Detection - Develop ML-based object detection and pose estimation
  4. Sensor Fusion - Integrate multiple sensor modalities for robust perception

Module Content​

Week 8: Isaac Sim Setup​

  • NVIDIA Isaac Sim installation
  • GPU requirements and optimization
  • ROS 2 bridge configuration
  • Scene creation and asset import

Week 9: Perception Pipeline​

  • Camera sensor simulation
  • Lidar point cloud processing
  • Object detection with deep learning
  • Pose estimation techniques

Week 10: Advanced Perception​

  • Multi-sensor fusion
  • Semantic segmentation
  • 6-DOF pose estimation
  • Real-time performance optimization

Capstone Integration​

Isaac Sim provides the perception pipeline for your humanoid:

  • Detect and localize objects in the environment
  • Estimate 6-DOF poses for manipulation
  • Fuse camera and lidar data
  • Generate semantic scene understanding

Assessment​

Isaac Perception Project (Week 10)

  • Multi-sensor perception system
  • Object detection and pose estimation
  • ROS 2 integration with Isaac Sim

Start with Week 8: Isaac Sim Setup →