Sistema de visão computacional com ROS para identificação e rastreamento de objetos em movimento em uma esteira industrial.

Abstract

Development of a computer vision system integrated with the Robot Operating System for identifying and tracking moving objects on an industrial conveyor belt. Using cameras and sensors, the system detects and tracks objects through fiducial markers, such as ArUco. The implementation was validated in a controlled environment, employing calibration methodologies and component integration, enabling robust and flexible automation for industrial production lines. The results indicate that the system is effective for real-time monitoring and classification of objects, contributing to the efficiency and adaptability of industrial operations.