ARDUINO Based Pick and Place Bot Using Image Detection

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Date

2024-07-13

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Daffodil International University

Abstract

The contemporary landscape of robotics is marked by the integration of smart technologies to enhance autonomy and utility. This thesis presents the development of an Arduino-Based Pick and Place Bot employing image detection, with mobile app control for versatile applications. The robot is equipped with a mobile-controlled mechanism, allowing users to navigate the bot through a mobile app interface. The pivotal feature lies in the real-time monitoring facilitated by a camera mounted on the robot, providing live feedback of its surroundings to the mobile app. The hardware foundation of this project comprises an Arduino board, motors for movement, and a camera for live imaging. The software infrastructure involves the Arduino Integrated Development Environment (IDE) and a mobile app development platform. The image detection algorithm implemented on the robot enables it to recognize and respond to objects in its vicinity. Through the mobile app, users can direct the robot's movements and collect objects from the environment. The realtime monitoring feature ensures a seamless and intuitive interaction, allowing users to make informed decisions based on the live visual feed. This thesis delves into the methodology of constructing the pick and place bot, detailing the hardware and software components, and the integration of image detection. The implementation phase includes a step-by-step guide, code snippets, and highlights of challenges encountered and solutions devised. Results demonstrate the robot's successful navigation, object recognition, and the efficacy of mobile control. In conclusion, this project contributes to the evolving field of robotics by presenting a practical application of Arduino-based automation, showcasing the potential for mobile-controlled pick and place bots with image detection capabilities in various contexts.

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Project report

Keywords

Image Detection, Robotics, Automation, Computer Vision

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