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Crane Workspace Mapping Using QR Codes

[+] Author Affiliations
M. Sazzad Rahman, Joshua Vaughan

University of Louisiana at Lafayette, Lafayette, LA

Paper No. DSCC2015-9823, pp. V002T30A004; 7 pages
doi:10.1115/DSCC2015-9823
From:
  • ASME 2015 Dynamic Systems and Control Conference
  • Volume 2: Diagnostics and Detection; Drilling; Dynamics and Control of Wind Energy Systems; Energy Harvesting; Estimation and Identification; Flexible and Smart Structure Control; Fuels Cells/Energy Storage; Human Robot Interaction; HVAC Building Energy Management; Industrial Applications; Intelligent Transportation Systems; Manufacturing; Mechatronics; Modelling and Validation; Motion and Vibration Control Applications
  • Columbus, Ohio, USA, October 28–30, 2015
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5725-0
  • Copyright © 2015 by ASME

abstract

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.

Copyright © 2015 by ASME
Topics: Cranes

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