HUMAN FOLLOWING CART

Abstract

The development of a human-following robot utilizing Raspberry Pi and camera technology represents a significant advancement in autonomous robotics, offering practical solutions for various industries. This project integrates a Raspberry Pi microcomputer, a camera, and ultrasonic sensors to create a robot capable of tracking and following a human operator. The system employs computer vision algorithms, facilitated by a Haar Cascade Classifier, to detect faces in real-time video feeds. The video feed is processed to determine the position of the human within the frame, enabling the robot to navigate accordingly. Ultrasonic sensors are used to measure the distance between the robot and the human, ensuring that a safe and optimal following distance is maintained. The motors and motor drivers are controlled based on the visual and distance data, allowing the robot to move forward, backward, or turn as needed. This combination of technologies enhances worker safety by reducing physical strain and improves operational efficiency by automating the transportation of goods, tools, and supplies. The implementation of this system demonstrates the practical application of affordable and accessible technologies like the Raspberry Pi in creating intelligent, autonomous robots. The project highlights the potential for such robots to revolutionize workflows in warehouses, manufacturing plants, and hospitals, making advanced automation more attainable for a wide range of businesses. The integration of computer vision and sensor-based navigation in human-following robots marks a significant step forward in the evolution of intelligent workspaces and autonomous systems.