Robot Arm Object Sorting System

Motivation?

This project was developed as part of my final third-year university project in collaboration with a team of passionate developers. The aim was to combine our knowledge of software development, hardware integration, and real-world problem-solving to build an innovative and functional system.

Why We Built This Project?

The primary goal was to design and implement a robot arm capable of sorting objects based on what an object detection system identifies. The project serves as a practical demonstration of how automation and machine learning can be applied to streamline tasks in industries like manufacturing, logistics, or recycling.

Problem It Solves?

Manual sorting processes are time-consuming, prone to error, and resource-intensive. This project automates the sorting process by detecting objects, identifying their characteristics (such as shape or color), and sorting them into predefined locations with precision. It’s a small-scale prototype showcasing the potential for industrial automation.

What I Learned?

Throughout this project, I gained invaluable experience in:

Python programming: Building the control logic for the robot arm. Flask: Developing a lightweight server for communication between the object detection system and the robot arm. Pico Microcontroller: Programming the hardware to execute precise movements. Team Collaboration: Working closely with other developers to integrate software and hardware components seamlessly.

What Makes This Project Stand Out?

Integration of Object Detection: The system uses a robust object detection model to classify items in real time. Dynamic Movement: The robot arm is highly responsive and moves objects to specified locations with accuracy. Full-Stack Implementation: Combines Python, Flask, and hardware programming for a comprehensive solution. Real-World Applicability: Demonstrates how automation can solve practical problems in various industries.