Notre avis
Ce modèle fournit une structure standardisée pour créer des exercices pratiques dans un manuel d'IA physique, avec des sections comme objectifs, instructions, vérification et défis.
Points forts
- Format clair et reproductible pour les exercices, réduisant l'effort de rédaction.
- Inclut des types d'exercices variés : expériences de pensée, simulations, intégration matérielle.
- Propose une progression de difficulté adaptée aux chapitres du manuel.
- Assure des critères de validation explicites et des temps estimés réalistes.
Limites
- Spécifique au manuel d'IA physique et aux technologies comme ROS 2, Jetson, RealSense.
- Peut nécessiter des ajustements pour d'autres domaines ou outils.
- Ne couvre pas la création de contenu de fond, seulement la structure d'exercice.
Utilisez ce modèle lorsque vous devez concevoir un exercice pratique standardisé pour un manuel technique en robotique ou IA physique.
Évitez ce modèle si vous rédigez du contenu théorique sans composante pratique ou si vous travaillez dans un domaine très différent de la robotique.
Analyse de sécurité
SûrThe skill contains only a template for educational exercises with benign ROS 2 commands. No destructive, exfiltrating, or obfuscated actions are present.
Aucun point d'attention détecté
Exemples
Create an exercise for Chapter 4 of the Physical AI textbook using the exercise-patterns skill. The exercise should be intermediate difficulty, about 30 minutes, and involve creating a ROS 2 publisher node that publishes joint states for a virtual robot arm.Use the exercise-patterns skill to outline a hardware integration exercise for Chapter 12. The student should deploy a ROS 2 node to a Jetson Orin Nano to read RealSense depth data and visualize it on a workstation. Include validation steps and a challenge to stream over Wi-Fi.Using the exercise-patterns skill, generate a thought experiment exercise for Chapter 1. Ask students to list five tasks that require physical embodiment which an LLM alone cannot accomplish. Include a difficulty of beginner and a time estimate of 15 minutes.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
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