Simulation / Robotics
AI Rover Challenge
A virtual rover, a teachable classifier, and a clear view of why the machine made its next move.
- React
- TypeScript
- Phaser
- Zustand
- Vitest / Playwright
What I contributed
Built the virtual rover workflow and interfaces for configuring components, teaching a classifier, programming rules and inspecting decisions.
What came out of it
Five browser missions in which students can run, pause, step and replay a rover, then examine its decisions and performance.
Robotics begins with cause and effect.
AI Rover Challenge gives secondary-school learners a way to explore robotics without physical robots, accounts or cloud services. They choose components, train a small classifier, write ordered control rules and run missions in a Singapore-inspired environment.
The learning journey follows the full loop: sense, analyse, decide, move, test and improve. Five missions introduce these ideas progressively, from movement and obstacle avoidance to AI-assisted control and a rescue challenge.
Build it, run it, understand it.
Component choices involve a budget and practical trade-offs. The AI lab exposes class balance and a confusion matrix. The programming lab turns an ordered IF/THEN list into readable pseudocode, while the simulator shows telemetry, sensor readings and a decision log.
My contribution brings those stages into one learning system. Learners can step through a run, rewind it and compare a changed design. Mission reports explain the outcome, and an engineering notebook keeps design decisions and reflections together.
The simulation has to stand on its own.
Simulation and rendering are separate layers. The same behaviour can be examined through the graphical scene or an accessible text grid when WebGL is unavailable. This makes the important engineering concepts usable on more of the machines a classroom may have.
The scoring model values completion, reliability, energy, safety and responsible AI alongside speed. Physical hardware integration is future adapter work; the current public project is a virtual simulator.
A learning environment that explains its decisions.
The public project includes the simulator, five missions, local progress storage, developer documentation and guides for students and educators. Its test suite covers simulation behaviour, scoring, rules and the workshop journey.
This is an independent public project with AMD-themed educational content. Compute comparisons in its technology corner are illustrative teaching material, rather than measurements of AMD products.