Robot Trajectory Tracking with Secret Sharing

Overview

This project implements a robot trajectory tracking system using two different secret-sharing techniques: Reed-Solomon and Shamir. The system simulates a robot tracking a reference trajectory and where the controller is executed on a set of N clouds. The proposed schemes try to handle missing and incorrect shares in control inputs computed by the clouds.

Features

• Custom Quantization: Implements a quantization method to handle floating-point values.
• Error Correction: Utilizes Reed-Solomon coding for robust control input reconstruction.
• Simulation: Simulates the robot's trajectory and computes position errors over time.
• Visualization: Generates plots for trajectory comparison, tracking errors, and share status.

Requirements

• Python 3.x
• NumPy
• Matplotlib
• RSSecretSharing Class (Developed by using https://github.com/mortendahl/privateml.)

Installation

1. Clone the repository:

   git clone <repository-url>
   cd <repository-directory>

2. Install the required packages:

   pip install numpy matplotlib

3. Ensure the RSSecretSharing library is available in your Python environment.

Usage

1. Prepare the reference trajectory files (xr.txt, yr.txt, thetar.txt) in the ./Reference Trajectories/ directory.

2. Run the simulation:

   python robot-code.py

3. The simulation will generate plots showing:

   • Robot trajectory vs. reference trajectory
   • Position errors over time
   • Share status table indicating errors and NaN values

Output

The following files will be generated in the working directory:

• trajectory_tracking_comparison.eps: A plot comparing the robot's trajectory with the reference trajectory.
• tracking_errors.eps: A plot showing the position errors over time.
• share_status_table.eps: A table visualizing the status of shares during the simulation.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.