Robotics Car Guidance System – Portfolio Showcase

Overview

The Robotics Car Guidance System was designed to autonomously navigate a barrier-filled track. Using a ranger sensor to detect distances and wheel encoders for turning precision, the car decides whether to move straight, turn clockwise, or counterclockwise. PWM motor control and H-Bridge drivers provide smooth and precise actuation.

Demo

Robotics car setup with sensor — The figure above is the path that we need to follow and lap around the track. The red box is the marker that I can signal the car with the ranger to turn a certain direction.

System Design — This high level diagram is our main code that demonstrate what our code would accomplish to complete the task. For more information, check the project documentation down below.

Equipment & Tools

Microcontroller & Peripherals

TI MSP430 (GPIO, timers, ISRs)
PWM motor control

Sensing

Ultrasonic ranger sensor
Wheel encoders

Actuation

DC motors
H-Bridge motor driver

Software Tools

Code Composer Studio (C programming)
Serial print debugging

Test Equipment

Track rulers/markers for validation

Technical Breakdown

Control Logic

Checks every 100 ms with ranger sensor input.
Ranger > 40 cm → drive straight.
Ranger ≤ 10 cm → 90° counterclockwise turn.
20 cm < ranger ≤ 40 cm → 90° clockwise turn.

Turning Implementation

Wheel encoders compute the arc length for 90° turns. H-Bridge GPIOs switch motor direction, and motors are disabled mid-turn for precision.

PWM Speed Control

Wheel speed regulated using PWM capture mode. Desired speed is constant, with error correction applied. Min/max duty cycles enforced for stability.

Challenges & Trade-offs

Ranger sensitivity: Fixed repeated turning issue with a 3-read delay loop.
Straight driving drift: Calibrated speeds for stability at higher values.
Abandoned bumper design: Simplified by moving to ranger sensing for turns.

Future Improvements

Optimize ranger frequency for smoother navigation.
Improve calibration for high-speed stability.
Add additional sensors (IR, LIDAR) for obstacle detection.
Implement wireless telemetry for live tracking.

What I Learned

Designing autonomous navigation with real-time feedback.
Applying PWM regulation and wheel encoders in practice.
Debugging ISR-driven embedded systems with sensor delays.
Understanding sensor fusion for reliable robotics control.

References

Full documentation, schematics, and experimental data are available in the project report.

🤖 Robotics Car Guidance System