Image Processing Based a Wireless Charging System with Two Mobile Robots

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 240)

Abstract

This paper presents the image processing algorithm for wireless charging between each mobile robot. The image processing algorithm converts Red Green Blue (RGB) format of inputted image to detect edge. It calculates a specific area using Hough Transformation (HT) in detected edge and judges correct charging antenna using Speeded-Up Robust Features (SURF). Accordingly, the image processing algorithm can control position and direction of mobile robot and antenna for wireless charging. The image processing algorithm is implemented wireless charging systems, which are set up on each two mobile robot and it is verified with experiment.

Keywords

Wireless charging HT SURF Mobile robot Color edge 

Notes

Acknowledgments

This research was supported by the The Ministry of Knowledge Economy (MKE), Korea, under the Information Technology Research Center (ITRC) support program (NIPA-2012-H0301-12-2007) supervised by the National IT Industry Promotion Agency (NIPA).

References

  1. 1.
    Wireless Power Consortium. http://www.wirelesspowerconsortium.com
  2. 2.
    Hough PVC (1962) Methods and means for recognizing complex patterns. US Patent 3,069,654Google Scholar
  3. 3.
    Bay H, Ess A, Tuytelaars T, Van Gool L (2008) SURF speeded up robust features. Comput Vis Imag Underst 110(3):346–359 Google Scholar
  4. 4.
    TETRA-DS DasaRobot, DasaRobot (2009)Google Scholar
  5. 5.
    Kim J-O, Rho S, Moon C-W, Ahn H-S (2012) Imaging processing based a wireless charging system with a mobile robot. Computer applications for database, education, and ubiquitous computing. Communications in computer and information science, vol 352. Springer, Heidelberg, pp 298–301Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht(Outside the USA) 2013

Authors and Affiliations

  1. 1.Department of Electronics EngineeringKookmin UniversitySeoulKorea

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