This report presents the development of a robotic arm for the efficient packaging of chocolates in a small-scale process. The robotic arm has a PRR (prismatic–rotational–rotational) configuration and uses a universal vacuum grip (UVG) to manipulate the chocolates with precision. Various materials and components were used, such as 3D-printed PLA parts for the mechanical elements and flexible TPU bands for optimal movement control. In terms of electronics, NEMA motors, an Arduino board, and a CNC interface were used for the precise control of the motors. The programming was conducted in Python and a graphical user interface (GUI) was created to manage the sequence of movements of the robotic arm. Key parameters, such as the accuracy in the placement of the chocolates, the grip strength, and the shape recovery ability were evaluated. The results demonstrate the successful integration of the robotic arm in the packaging process, achieving an efficient and consistent placement of the chocolates in the plastic trays. This project highlights the importance and potential of automation in the food packaging industry, by improving productivity, reducing human error, and ensuring packaging quality. The knowledge and results obtained in this project contribute to the field of robotics.

This paper details the development of an advanced robotic arm designed to package chocolates efficiently in a smallscale process. The arm features a Prismatic-Revolute-Revolute configuration and is equipped with a Universal Vacuum Grip to handle chocolates precisely. Its construction utilizes PLA 3D printed parts for the mechanical structure and flexible TPU belts to ensure optimal movement control. Electronically, the system is powered by NEMA 17 motors, controlled by an Arduino board and a CNC interface for precision motor management. The programming, conducted in Python, integrates artificial intelligence through computer vision techniques to enhance the accuracy and adaptability of the packaging process. A graphical user interface was developed, allowing intuitive control and sequence management of the robotic arm's operations. The incorporation of artificial intelligence enabled the robotic arm to identify successfully and sort chocolates of varying types, greatly enhancing packaging efficiency. The results demonstrate the arm's capability to consistently place chocolates in trays, thereby augmenting productivity, reducing human error, and maintaining packaging quality. This project underscores the significance and potential of integrating automation and artificial intelligence in the food packaging industry.