| name | exercise-patterns |
| description | Structure for creating hands-on exercises in the Physical AI textbook. |
Exercise Template (Strict Format)
## Exercise X.Y: [Title]
**Difficulty**: [Beginner | Intermediate | Advanced]
**Time**: [15 min | 30 min | 1 hour | 2 hours]
**Hardware**: [Workstation | Jetson + RealSense | Unitree Robot]
### Objectives
By completing this exercise, you will:
- [Action verb] [specific skill] (e.g., "Create a ROS 2 publisher node")
- [Action verb] [specific skill] (e.g., "Visualize sensor data in RViz2")
- [Action verb] [specific skill] (e.g., "Deploy code to Jetson Orin Nano")
### Prerequisites
- Chapter X completed
- ROS 2 Humble installed
- [Specific hardware setup, e.g., "RealSense D435i connected"]
### Instructions
#### Step 1: [Action]
```bash
# Command to run
ros2 pkg create my_package --build-type ament_python
Expected Output:
Successfully created package 'my_package'
Step 2: [Action]
[Detailed instructions with code snippets]
Step 3: [Verification]
Run this command to verify:
ros2 topic list
Expected: You should see /my_topic in the list.
Validation Checklist
- Code compiles without errors (
colcon build) - Node runs and publishes data (
ros2 topic echo /my_topic) - RViz2 displays data correctly
Challenge (Optional)
[Extended task for advanced students, e.g., "Modify the node to publish at 100 Hz instead of 10 Hz"]
Troubleshooting
Problem: "Package not found"
Solution: Source your workspace (source install/setup.bash)
Problem: "Topic not visible"
Solution: Check if node is running (ros2 node list)
## Exercise Types
### 1. Thought Experiment (No Code)
**Format**: Conceptual questions to build intuition
**Example**: "List 5 tasks that require physical embodiment that an LLM alone cannot do"
### 2. Simulation Task (Gazebo/Isaac Sim)
**Format**: Code + Launch files + Gazebo world
**Example**: "Spawn a humanoid in Gazebo and make it walk forward 2 meters"
### 3. Hardware Integration (Jetson + Sensors)
**Format**: Deploy ROS 2 node to Jetson, read sensor data
**Example**: "Stream RealSense depth images to your workstation via Wi-Fi"
### 4. Capstone Project (Multi-Week)
**Format**: Complete system with milestones
**Example**: "Build an autonomous room-cleaning robot"
## Progressive Difficulty Curve
**Beginner** (Chapters 1-5):
- Copy-paste code examples
- Run pre-built packages
- Simple parameter changes
**Intermediate** (Chapters 6-15):
- Modify existing code
- Create new nodes
- Integrate multiple sensors
**Advanced** (Chapters 16-28):
- Design complete systems
- Optimize for hardware (Jetson)
- Implement novel algorithms
- Deploy to real robots
## Validation Standards
Every exercise must have:
1. **Clear Success Criteria** - "You should see X" or "The robot should do Y"
2. **Runnable Code** - Copy-paste should work without modification
3. **Hardware Note** - Explicitly state if Jetson/Robot required
4. **Time Estimate** - Realistic completion time for average student