🤖 5DOF Bioprinter & Robotics Control – MATLAB & Arduino Integration

📌 Introduction

This project contains a collection of MATLAB scripts and Arduino sketches developed for simulating, controlling, and testing a 5‑Degree‑of‑Freedom (DOF) robotic bioprinter and related mechatronic systems.
It demonstrates expertise in robot kinematics, computer vision, dynamic simulation, and microcontroller‑based hardware control — from algorithm design to real‑time implementation.

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⚙️ Project Components

🔹 MATLAB Scripts

• DirectKinematicsBasic.m – Calculates forward kinematics for a 5DOF manipulator.
• TriangulatedImages.m – Processes static images for 3D position estimation via triangulation.
• TriangulatedLiveCamera.m – Captures and processes live camera feeds for real‑time 3D localization.
• doublePendulumBasic.m – Simulates the dynamics of a double pendulum system.
• doublePendulumLiveCamera.m – Tracks and analyzes a physical pendulum setup via camera input.
• simulation.m / simulationpart2.m – Full system simulations integrating mechanical models and control logic.

🔹 Arduino Sketches

• bingo_doublependulum.ino – Drives sensors/actuators for a double pendulum test platform.
• bingo_pendulum.ino – Single pendulum setup with real‑time data acquisition.
• verifyPCA9685.ino – Tests PCA9685 PWM driver functionality for servo control.

🔹 Other Files

• CreatingNetworkSocket – Network communication setup for remote control or data streaming between systems.

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📊 Key Deliverables

• Forward kinematics implementation for custom 5DOF robotic arm.
• Real‑time camera triangulation for object position tracking.
• Simulations of dynamic systems (pendulums, robotic motion).
• Verified microcontroller firmware for actuator control and sensor integration.
• Modular code adaptable to other robotics platforms.

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✅ Conclusion

This repository showcases:

• Integration of MATLAB‑based simulation and vision processing with Arduino hardware control.
• Application of robotics theory (kinematics & dynamics) to functional prototypes.
• Experience bridging simulation, embedded systems, and real‑time data acquisition.

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💻 Tech Stack

• MATLAB (Simulations, computer vision, kinematics)
• Arduino C/C++ (Microcontroller programming)
• PCA9685 PWM Driver (Servo control)
• Camera systems for real‑time object tracking

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📈 Next Steps

• Implement inverse kinematics for precise end‑effector positioning.
• Integrate closed‑loop control with sensor feedback.
• Expand live vision tracking to multi‑object scenarios.
• Prepare documentation for full bioprinting pipeline integration.

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🤝 Contact

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