AI Based Robotic Arm for Color Sorting Object

Color sorting robotic arms have improved industrial automation by making material handling more accurate, efficient and productive. This paper explores the development of a robotic arm system that identifies and sorts objects based on their colors. Utilizing a ready-made robotic arm, an Arduino Uno microcontroller, and an OpenCV-based color detection system, the project aims to automate the sorting process by placing detected objects into designated containers. The system integrates a camera module, servo motors, and a color recognition algorithm to ensure accurate sorting. The research outlines the methodology, hardware and software implementation, circuit design, and overall system performance. This project not only demonstrates an advanced implementation of robotic automation but also highlights the significance of embedded systems in industrial applications. The robotic arm operates by capturing real-time images of objects, processing color information, and executing precise movements to place items into appropriate bins. The proposed system is a step toward enhancing smart manufacturing processes, reducing human intervention, and improving sorting efficiency in industries like recycling, food processing, and logistics. The research findings illustrate the system’s accuracy, limitations, and potential improvements. Additionally, future developments, such as integrating machine learning for enhanced object classification and expanding the system’s capabilities, are discussed. This paper serves as a comprehensive guide for future researchers and engineers aiming to develop automated sorting mechanisms.