About an Error Correcting Method of ArUco Markers Considering Row Data for a Mobile Robot

In the context of Industry 4.0, the transition from high-volume, low-variety to low-volume, high-variety production systems emphasizes the need for advanced mobile robots with precise self-localization capabilities. A widely used tool for robot position calculation is the ArUco marker. This paper introduces a novel error-correcting method for ArUco markers that addresses limitations of existing techniques by applying error correction on a row-by-row basis. Experimental results demonstrate that this approach significantly improves the robustness of ArUco marker recognition during robot movement. The proposed method enhances recognition accuracy in challenging conditions, such as those involving blurring, by refining the detection process for greater reliability in dynamic environments.