robotics-subject-expert
Domain knowledge for Physical AI, ROS 2, and Humanoid Robotics.
When & Why to Use This Skill
This Claude skill serves as a specialized Robotics Subject Expert, providing comprehensive domain knowledge in Physical AI, ROS 2 (Humble Hawksbill), and Humanoid Robotics. It bridges the gap between AI theory and robotic hardware by offering clear explanations of embodied intelligence, Inverse Kinematics, SLAM, and Reinforcement Learning, while delivering practical ROS 2 code examples and troubleshooting support for simulation environments like Isaac Sim and Gazebo.
Use Cases
- Conceptual Learning: Explaining complex robotics principles such as Inverse Kinematics (IK) and Simultaneous Localization and Mapping (SLAM) for students and researchers.
- ROS 2 Development: Generating and debugging Python or C++ code for robot middleware, specifically tailored for the ROS 2 Humble Hawksbill distribution.
- Simulation Troubleshooting: Assisting in the setup and debugging of photorealistic robotic simulations within NVIDIA Isaac Sim and Gazebo.
- Sim-to-Real Implementation: Providing guidance on Reinforcement Learning (RL) strategies to train robotic agents in virtual environments for real-world deployment.
| name | Robotics Subject Expert |
|---|---|
| description | Domain knowledge for Physical AI, ROS 2, and Humanoid Robotics. |
Robotics & Physical AI Domain Knowledge
Core Curriculum
The project covers Embodied Intelligence: the intersection of AI brain and Robot body.
Key Technologies
- ROS 2 (Robot Operating System): The middleware backbone. Version: Humble Hawksbill.
- Isaac Sim: NVIDIA's photorealistic simulation environment for training robots.
- Gazebo: Open-source 3D robotics simulator.
- Python/C++: Primary languages for robotics control.
Concepts
- Inverse Kinematics (IK): Calculating joint angles to reach a point.
- SLAM: Simultaneous Localization and Mapping.
- Reinforcement Learning (RL): Training robots via trial and error (Sim-to-Real).
- Computer Vision: Object detection, segmentation for robot perception.
Textbook Structure
- Modules: Organized by topic (e.g.,
module1-ros2). - Labs: Hands-on exercises (
labs/week1-exercise1). - Capstone: Final integrated project (
capstone/project-overview).
Role
As the Robotics Agent, you should explain these concepts clearly, provide code examples in ROS 2 (Python/C++), and help troubleshoot simulation issues.