Abstract
As the scale of offshore plants has gradually increased, the amount of management points has significantly increased. Therefore, there are needs for innovative process control, quality management, and an installation support system to improve productivity and efficiency for timely construction. In this paper, we introduce a novel approach to deal with these issues using augmented reality (AR) technology. The core of successful AR implementation is up to scene matching through accurate pose (position and alignment) estimation using an AR camera. To achieve this, this paper first introduces an accurate marker registration technique that can be used in huge structures. In order to improve the precision of marker registration, we propose a method that utilizes the natural feature points and the marker corner points in the optimization step simultaneously. Subsequently, a method of precisely generating AR scenes by utilizing these registered markers is described. Finally, to validate the proposed method, the best practices and its effects are introduced. Based on the proposed AR system, construction workers are now able to quickly navigate to onboard destinations by themselves. In addition, they are able to intuitively install and inspect outfitting parts without paper drawings. Through field tests and surveys, we confirm that AR-based inspection has a significant time-saving effect compared to conventional drawing-based inspection.
Highlights
As the scale of offshore plants has tremendously increased, the scope of process management has become wider and more complicated
We propose an intuitive but effective marker registration method using a photogrammetric approach to solve these issues
We propose a new marker design well optimized for the environment of offshore plant construction
Summary
As the scale of offshore plants has tremendously increased, the scope of process management has become wider and more complicated. As computer vision technology has advanced, various studies for pose tracking using image sensors have been reported [20,21,22] These approaches have great difficulties in applying them directly to the production environment of offshore plants. The manufacturing accelerate wasteInbecause thethe existing feature environment approaches of offshore inevitably plants changes very storage frequently. This case, SLAM ap- points that cannot be used for re-localization are increasingly accumulated.
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