About this page
Every project you see here is a chapter of my journey. Each one was built from scratch — driven by curiosity, fueled by persistence, and sharpened by real challenges. These aren’t just technical tasks, they’re reflections of growth, experimentation, and vision. Whether it's an autonomous robot or a complex circuit design, every build is a step toward mastering my craft and making an impact. I share them here not just to showcase what I’ve done — but to inspire what’s possible.
⬅ Projects
🔧 Project Overview
MARV (Microcontroller‑based Autonomous Robotic Vehicle) is a self‑navigating,
sensor‑driven robotic vehicle developed as part of the EMK310 module. The aim of
the project was to integrate embedded systems, sensor interfacing, and actuator
control into a compact mobile platform capable of intelligent autonomous
behaviour. The vehicle is designed to navigate a course, detect colours, and make
decisions based on real‑time sensor data—simulating applications in line‑following
robots, factory automation, and mobile IoT systems.
🎯 Objectives
Design and construct an autonomous robot platform.
Interface various sensors including a photodiode‑based colour sensor.
Implement signal processing and control logic using a microcontroller.
Perform real‑world testing and optimise performance through iterative calibration.
⚙️ System Architecture
🧠 Microcontroller: PIC or ATmega handles sensor acquisition, ADC,
decision logic, and motor PWM.👁️ Sensor Suite: Custom photodiode + RGB LED array detects five
colours via a transimpedance amplifier (TIA).🔦 Lighting Array: RGB LEDs 3 mm above track ensure consistent illumination.🔋 Power & Motors: Dual DC motors with H‑bridge driver and regulated battery supply.
🧱 Mechanical Design
Chassis designed in CAD and 3‑D printed in PLA. The sensor housing mimics a V6
engine: angled arms align the RGB LED array and photodiode symmetrically,
maintaining a constant 3 mm gap over the track while shielding ambient light.
🧪 Testing & Validation
Oscilloscope readings captured distinct voltage signatures for black, white, red,
green, and blue surfaces. These thresholds were built into firmware logic. Track
runs under varying lighting proved stable after iterative calibration.
📈 Results
Achieved reliable real‑time colour detection with clear voltage separation
between five colours, enabling robust line‑following and decision‑making.
💡 Challenges & Solutions
Challenge Solution Low photodiode current TIA with 1 MΩ feedback + 10 pF capacitor Ambient‑light interference Enclosed, focused sensor casing Noise / oscillations Filtering capacitor & grounded shielding
🧠 Engineering Concepts Demonstrated
Photodiode + TIA analog circuit design
Two‑port network analysis
Embedded Assembly programming for sensor integration
PWM motor control & navigation logic
Mechanical CAD and rapid prototyping
🌐 Conclusion
The MARV project demonstrates the integration of hardware, firmware, and mechanical
systems into a unified, functional autonomous robot. It showcases practical
engineering skills in sensor interfacing, analog circuit design, embedded control,
and mechanical fabrication—laying a strong foundation for more complex autonomous
robotic systems.
