Differential-Robot-Control-RPP-PID

This project simulates a three-wheeled differential drive robot performing trajectory tracking using the RPP (Regulated Pure Pursuit) Law for path following and auto-tuning PID controllers for motor speed regulation.

Project Overview

The simulation focuses on a differential drive system where the motors are identified using system identification techniques to obtain the transfer functions for both left and right wheels.

Key Features:

• System Identification: Motor dynamics are characterized by coefficients $a_1, a_2, b_1, b_2$ for precise control.
• Path Following: Implementation of the RPP Law to guide the robot along a predefined trajectory.
• Low-level Control: Dual PID controllers for independent motor speed synchronization.
• Trajectory: Rectangular path tracking.

System Architecture

1. Trajectory Generator: Inputs a custom rectangular path.
2. Kinematic Controller (RPP): Calculates required linear ($v$) and angular ($\omega$) velocities.
3. Dynamic Controller (PID): Adjusts motor voltages based on the identified $a, b$ coefficients.

How to Run

To run the simulation, follow these steps in MATLAB:

1. Open the project folder.
2. Run init.m to load parameters, identified coefficients, and controller gains.
3. Run sim_result.m to visualize the performance graphs.

Results and Analysis

The simulation provides the following output plots:

• Robot's Trajectory: 2D mapping of the robot's movement vs. reference path.
• Cross-track Error: Deviation from the planned trajectory.
• Heading Angle: Orientation of the robot over time.
• Velocity Profiles: Both Linear and Angular velocities.

References

This project implements the Regulated Pure Pursuit algorithm as described in:

• S. Macenski, S. Singh, F. Martin, J. Gines, "Regulated Pure Pursuit for Robot Path Tracking," Autonomous Robots, 2023.

Technologies Used

• MATLAB & Simulink
• System Identification Toolbox
• Control System Toolbox