Crane workspace mapping using qr codes

M. Sazzad Rahman, Joshua Vaughan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a novel approach of mapping a crane workspace using a combination of QR code-based and imagesegmentation- 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-segmentationbased 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.

Original languageEnglish
Title of host publicationDiagnostics 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
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791857250
DOIs
StatePublished - 2015
Externally publishedYes
EventASME 2015 Dynamic Systems and Control Conference, DSCC 2015 - Columbus, United States
Duration: Oct 28 2015Oct 30 2015

Publication series

NameASME 2015 Dynamic Systems and Control Conference, DSCC 2015
Volume2

Conference

ConferenceASME 2015 Dynamic Systems and Control Conference, DSCC 2015
Country/TerritoryUnited States
CityColumbus
Period10/28/1510/30/15

Fingerprint

Dive into the research topics of 'Crane workspace mapping using qr codes'. Together they form a unique fingerprint.

Cite this