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      • Department of Electrical and Electronics Engineering
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      Surface differentiation and localization by parametric modeling of infrared intensity scans

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      Author
      Aytaç, Tayfun
      Barshan, Billur
      Date
      2005
      Source Title
      Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2005
      Publisher
      IEEE
      Pages
      2294 - 2299
      Language
      English
      Type
      Conference Paper
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      Abstract
      In this study, surfaces with different properties are differentiated with simple low-cost infrared (IR) emitters and detectors in a location-invariant manner. The intensity readings obtained from such sensors are highly dependent on the location and properties of the surface, which complicates the differentiation and localization process. Our approach, which models IR intensity scans parametrically, can distinguish different surfaces independent of their positions. The method is verified experimentally with wood, Styrofoam packaging material, white painted wall, white and black cloth, and white, brown, and violet paper. A correct differentiation rate of 100% is achieved for six surfaces and the surfaces are localized within absolute range and azimuth errors of 0.2 cm and 1.1°, respectively. The differentiation rate decreases to 86% for seven surfaces and to 73% for eight surfaces. The method demonstrated shows that simple IR sensors, when coupled with appropriate processing, can be used to differentiate different types of surfaces in a location-invariant manner.
      Keywords
      Surface differentiation
      Infrared sensors
      Position estimation
      Lambertian reflection
      Feature extraction
      Permalink
      http://hdl.handle.net/11693/27305
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/IROS.2005.1545319
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      • Department of Electrical and Electronics Engineering 3524
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