The present study proposes a fiducial marker for location systems that uses computer vision. The marker employs a set of tape-shaped markers that facilitate their positioning in the environment, allowing continuous reading to cover the entire perimeter of the environment and making it possible to minimize interruptions in the location service. Because the marker is present throughout the perimeter of the environment, it presents hierarchical coding patterns that allow it to be robust against multiple detection scales. We implemented an application to help the user generate the markers with a floor plan image. We conducted two types of tests, one in a 3D simulation environment and one in a real-life environment with a smartphone. The tests made it possible to measure the performance of the tape-shaped marker with readings at multiple distances compared to ArUco, QRCode, and STag with detections at distances of 10 to 0.5 m. The localization tests in the 3D environment analyzed the time of marker detection during the journey from one room to another in positioning conditions (A) with the markers positioned at the baseboard of the wall, (B) with the markers positioned at camera height, and (C) with the marker positioned on the floor. The localization tests in real conditions allowed us to measure the time of detections in favorable conditions of detections, demonstrating that the tape-shaped-marker-detection algorithm is not yet robust against blurring but is robust against lighting variations, difficult angle displays, and partial occlusions. In both test environments, the marker allowed for detection at multiple scales, confirming its functionality.

Na Onda do Pitiú: Uma Abordagem de Educação Ambiental Gamificada no Contexto Amazônico / On the Pitiú Wave: An Approach to Gamified Environmental Education in the Amazonian Context

Applications using fiducial markers have evolved across sectors such as industry, health, and education. Markers are effective because their highly distinguishable visual patterns and varied morphologies allow for high-accuracy pose estimation. However, designing a robust fiducial marker system is difficult and requires specific strategies to ensure reliability for applications such as photogrammetry and robot localization. This study aims to address this challenge through a systematic study of 88 articles selected using snowball methodology. This study focused on marker design characteristics to analyze different types of robustness. The goal of this study was to formally define fiducial markers, explore their intrinsic and extrinsic characteristics, and produce a taxonomy covering morphological and algorithmic aspects. The primary outcome is a comprehensive taxonomy and theoretical framework that provides best practices, guiding researchers in developing or employing robust fiducial markers tailored to their specific applications.