Welcome to the Real-Time Trajectory tracking Leaderboard. This repository evaluates your trajectory performance using RMSE (Root Mean Square Error) in Practice 6, Mechatronics (11642) - Universitat Politècnica de València.
The goal is to achieve the best trayectory tracking with your mobile robot..
You can monitor the competition results and the latest submission plot here: 👉 [Competition Results]
- Tune your controller: Adjust your strategy and parameters on the mobile robot and run the trajectory.
- Upload your data from the robot: Save your test results into a
.txtfile.- Important: Your file must follow the standard export format (already made by the robot).
- Submit the Form: Upload your file and enter your name in the official submission form: [GOOGLE FORM]
To ensure the automated judge can read your results, your CSV file must have the following structure (Standard Robot Export):
| Column | Data Description | Units |
|---|---|---|
| A | Reference trajectory X | cm |
| B | Reference trajectory Y | cm |
| C | Real trajectory X | cm |
| D | Real trajectory Y | cm |
| E | RMS Error | cm |
Caution
Do not change the order of the columns. The evaluation script relies on these exact positions to calculate your score.
We use the Root Mean Square Error to rank your performance.
- A lower RMSE means better tracking and higher precision.
- The Grade is automatically calculated based on your RMSE (Max: 10.00).
- Python: Data processing and plotting (Pandas, Numpy, Matplotlib).
- GitHub Actions: Automated CI/CD pipeline for real-time assessment.
- Google Forms & Apps Script: Student submission bridge.
- Tailwind CSS: Live dashboard visualization.
Good luck and may the best controller win! 🤖🏎️