Course Modules
Weeks 3-5
Module 1: The Robotic Nervous System (ROS 2)
Master ROS 2 architecture, communication patterns, and robot modeling. Learn to build distributed robotic systems using nodes, topics, services, and actions.
Learning Outcomes:
- Explain the ROS 2 computation graph and its components
- Create publishers, subscribers, and service clients using rclpy
- Define robot structure using URDF and visualize in RViz2
Weeks 6-7
Module 2: Digital Twins - Simulation & Sensors
Build digital twins for robotic systems using Gazebo and Unity. Simulate sensors, physics, and environments for testing before deploying to physical hardware.
Learning Outcomes:
- Create Gazebo simulation environments with physics and sensors
- Integrate Unity for photorealistic sensor simulation
- Test navigation and perception algorithms in simulation
Weeks 8-10
Module 3: NVIDIA Isaac - Perception & Navigation
Leverage NVIDIA Isaac Sim for GPU-accelerated robotics. Implement VSLAM, Nav2 navigation stacks, and reinforcement learning for autonomous behaviors.
Learning Outcomes:
- Set up and configure NVIDIA Isaac Sim environments
- Implement Visual SLAM for robot localization
- Deploy Nav2 navigation stack for autonomous navigation
Weeks 11-13
Module 4: VLA & Humanoid Robotics
Integrate Vision-Language-Action models with humanoid robots. Master humanoid kinematics, manipulation, and conversational AI for natural human-robot interaction.
Learning Outcomes:
- Calculate forward and inverse kinematics for humanoid robots
- Implement manipulation primitives for pick-and-place tasks
- Integrate conversational AI with robot action planning
Recent Updates
2025-11-29
Textbook Structure Initialized
Complete textbook structure with 4 modules and dashboard homepage is now live.
2025-11-29
Setup Guides Available
Hardware setup guides for Workstation, Edge Kit, and Cloud are now available.