CODING PATH C
AI Pose Rescue Game
Train a Google Teachable Machine Pose Classification model and use body movements to control a rescue game character in MRT AI Studio.
Your Mission π―
Train a Pose Classification model using Google Teachable Machine, then connect it to MRT AI Studio to create a rescue game controlled by your body movements.
For example: raise your arms to make the character jump over collapsed debris, lean left to dodge falling rocks, or hold a stop pose to halt before a danger zone.
π‘ This is not about adding AI as decoration β AI must be the primary control method for your game character.
AI Requirements π€
| Item | Requirement |
|---|---|
| AI Model | Google Teachable Machine β Pose Project only |
| Minimum Poses | At least 3 distinct poses (4+ recommended) |
| Game Platform | MRT AI Studio (block coding) |
| Not Accepted | Image Classification or Sound Classification as main control |
| Not Allowed | External ML frameworks (TensorFlow, PyTorch, etc.) |
Pose Control Examples πΉοΈ
| Pose | Game Action |
|---|---|
| Both arms raised | Jump or send rescue signal |
| Lean right | Move right |
| Lean left | Move left |
| Hand pushed forward | Stop |
| One hand raised | Request rescue |
| Crouching | Duck under obstacles |
Project Examples π‘
| Project | Description |
|---|---|
| AI Escape Game | Control a character with body movements to escape a collapsing highway zone |
| AI Rescue Signal Game | Recognise specific poses to send rescue signals from a disaster zone |
| AI Obstacle Dodge | Use poses to dodge falling rocks, cracks, and debris |
| AI Supply Delivery | Control a drone/character via body movements to deliver rescue supplies |
| AI Safety Training | An educational game that teaches correct rescue signal poses |
Allowed Tools π οΈ
β
MRT AI Studioβ
Google Teachable Machine (Pose only)
Not allowed as main control:
Image ClassificationSound ClassificationTensorFlow / PyTorchScratch (scratch.mit.edu)Unity / Python / JavaScript
Evaluation Criteria π
| Criteria | Beginning (1) | Developing (2) | Accomplished (3) | Exemplary (4) | Weight |
|---|---|---|---|---|---|
| AI Model Quality | Model doesn’t recognise poses | Recognises 1β2 poses inconsistently | Recognises 3+ poses accurately | Stable, diverse training data, 4+ poses | Γ5 = 20 |
| Game Design | No clear game goal | Basic concept, limited interaction | Clear mission, obstacles, scoring | Polished game with levels and progression | Γ5 = 20 |
| Theme Connection | Not related to theme | Loosely related | Clear rescue scenario | Thoughtful, realistic rescue design | Γ5 = 20 |
| Technical Integration | AI not connected | Partial connection, unstable | AI controls game actions reliably | Seamless AI-to-game integration | Γ5 = 20 |
| Presentation | No explanation | Brief or unclear | Clear demo of AI + game | Excellent walkthrough of AI training + gameplay | Γ4 = 20 |
Total: 100 points
How to Get Started π
All AI training guides, MRT AI Studio tutorials, Teachable Machine Pose setup instructions, project examples, and submission guidelines are provided through the MRT eLearning courses after registration.
- Register and access the eLearning platform
- Complete the AI Pose training course
- Create your Pose model on Google Teachable Machine
- Build your rescue game in MRT AI Studio
- Connect your Pose model to the game
- Test, improve, and refine
- Record your 3-minute demo video
- Submit via the Manager Dashboard
π Students do not need to choose their category during registration. Submit when your project is ready.
Submission Requirements π¦
- A video link (YouTube Unlisted) β max 3 minutes
- A Teachable Machine model URL
- A short description (300+ characters)
- Game file or project link (optional)
πΉ Your video should show the AI pose training process AND the live gameplay demo. Voice explanation by the student is strongly recommended.
Australian Curriculum Connections π¦πΊ
| Curriculum Area | Connection |
|---|---|
| Digital Technologies | AI model training, data collection, input/output, algorithmic game control, digital solution creation |
| Mathematics | Data classification, accuracy analysis, patterns, conditional logic |
| Health & PE | Body awareness, movement, pose recognition, physical engagement |
| Critical & Creative Thinking | Designing AI-controlled solutions, evaluating model performance |
| Digital Literacy | Using AI tools, managing digital projects, understanding data privacy |
Aligned with Australian Curriculum V9.0
“Train your AI. Move your body. Save lives through code.”
