Optimized methodologies for augmented reality markers based localization

Wingkwong Chung, Ning Cui, Xu Chen, Tin Lun Lam, Yangsheng Xu, Yongsheng Ou

Abstract: Localization is one of the key research topics in robotics. Although computer vision based methodologies such as Augmented Markers provides a realtime localization approach, the sensing range and localization accuracy are the main limitations for applications. In this paper, we proposed the use of a problem solving tool, TRIZ to overcome these limitations. Among the tools provided by TRIZ, we illustrated the selection of principles for problem solving. To enhance the sensing range, a novel AR marker is presented. To improve the localization accuracy, we presented the use of an AR polyhedron for system localization. With the use of an AR cube for illustration, we further developed a new optimization strategy. It is a weighted sum method which aims to optimize the position of the AR cube by considering the orientation of different AR markers captured by a camera. To evaluate the proposed methods, different experiments have been conducted including static and dynamic localizations. Results show that the proposed solutions and strategy can significantly improve the sensing range and accuracy of the conventional AR localization system.