This paper presents a novel approach of mapping a crane workspace using a combination of QR code-based and image-segmentation-based mapping algorithms. Known objects in the workspace are labeled with a QR code, and a database contains the information of the objects. A camera mounted on the crane trolley takes pictures as the crane moves through the workspace. The images are then used to produce an image-segmentation-based map of the workspace. To produce the QR code-based map, the QR codes in the images taken with the camera are decoded, and the information of the corresponding objects are read from the database file. The object position and orientation are calculated from the position and orientation of the QR codes, and the map is drawn. Results showed that the mapping algorithms are more reliable together than they are individually.
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