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Research to improve the performance of self localization of mobile robot utilizing video information of CCTV

CCTV 영상 정보를 활용한 이동 로봇의 자기 위치 추정 성능 향상을 위한 연구

  • Park, Jong-Ho (Department of Electrical & Electronic Engineering, Seonam University) ;
  • Jeon, Young-Pil (Department of Electronic Engineering, Chonbuk National University) ;
  • Ryu, Ji-Hyoung (Department of Electronic Engineering, Chonbuk National University) ;
  • Yu, Dong-Hyun (Department of Electronic Engineering, Chonbuk National University) ;
  • Chong, Kil-To (Department of Electronic Engineering, Chonbuk National University)
  • 박종호 (서남대학교 전기전자공학과) ;
  • 전영필 (전북대학교 전자공학부) ;
  • 류지형 (전북대학교 전자공학부) ;
  • 유동현 (전북대학교 전자공학부) ;
  • 정길도 (전북대학교 전자공학부)
  • Received : 2013.10.17
  • Accepted : 2013.12.05
  • Published : 2013.12.31

Abstract

The indoor areas for the commercial use of automatic monitoring systems of mobile robot localization improves the cognitive abilities and the needs of the environment with this emerging and existing mobile robot localization, and object recognition methods commonly around its great sensor are leveraged. On the other hand, there is a difficulty with a problem-solving self-location estimation in indoor mobile robots using only the sensors of the robot. Therefore, in this paper, a self-position estimation method for an enhanced and effective mobile robot is proposed using a marker and CCTV video that is already installed in the building. In particular, after recognizing a square mobile robot and the object from the input image, and the vertices were confirmed, the feature points of the marker were found, and marker recognition was then performed. First, a self-position estimation of the mobile robot was performed according to the relationship of the image marker and a coordinate transformation was performed. In particular, the estimation was converted to an absolute coordinate value based on CCTV information, such as robots and obstacles. The study results can be used to make a convenient self-position estimation of the robot in the indoor areas to verify the self-position estimation method of the mobile robot. In addition, experimental operation was performed based on the actual robot system.

Keywords

External Image;Localization;Marker;Mobile Robot

Acknowledgement

Supported by : 한국연구재단

References

  1. Sebum Chun, et al, "Estimation of Precise Relative Position using INS/Vision Sensor Integrated System", Journal of the Korean Society for Aeronautical and Space Sciences, Vol.36 No.9, pp. 891-897, 2008. DOI: http://dx.doi.org/10.5139/JKSAS.2008.36.9.891 https://doi.org/10.5139/JKSAS.2008.36.9.891
  2. http://kr.engadget.com/2011/03/15/tango-view/
  3. A. Ess, et al, "A mobile vision system for robust multi-person tracking", CVPR, pp. 1-8, IEEE, 2008. DOI: http://dx.doi.org/10.1109/CVPR.2008.4587581 https://doi.org/10.1109/CVPR.2008.4587581
  4. Jae-Kyung Lee and Young-Hwan Park, "Localization of Mobile Robot using Active Landmark", Journal of KAIS, Vol. 9, No. 1, pp. 64-69, 2008. DOI: http://dx.doi.org/10.5762/KAIS.2008.9.1.064 https://doi.org/10.5762/KAIS.2008.9.1.064
  5. M.M.Y. Chang and K.H. Wong, "Model reconstruction and pose acquisition using extended Lowe's method", IEEE Transactions on Multimedia, Vol. 7, No. 2, pp. 253-260, 2005. DOI: http://dx.doi.org/10.1109/TMM.2005.843344 https://doi.org/10.1109/TMM.2005.843344
  6. Sung-Ki Kwon, et al, "A Study of Compensation Algorithm for Localization based on Equivalent Distance Rate using Estimated Location", Journal of KAIS, Vol. 11, No. 9, pp. 3571-3577, 2010. DOI: http://dx.doi.org/10.5762/KAIS.2010.11.9.3571 https://doi.org/10.5762/KAIS.2010.11.9.3571
  7. Ji-Hyoung Ryu, et al, "The navigation method of mobile robot using a omni-directional position detection system", Journal of KAIS, Vol. 10, No. 2, pp. 237-242, 2009. DOI: http://dx.doi.org/10.5762/KAIS.2009.10.2.237 https://doi.org/10.5762/KAIS.2009.10.2.237
  8. Sung-Hwa Hong, Seok-Yong Jung, "Localization Algorithm in Wireless Sensor Networks using the Acceleration sensor", Journal of KAIS, Vol. 11, No. 4, pp. 1294-1300, 2010. DOI: http://dx.doi.org/10.5762/KAIS.2010.11.4.1294 https://doi.org/10.5762/KAIS.2010.11.4.1294
  9. Camera Calibration Toolbox for Matlab, http://www.vision.caltech.edu/bouguetj/calib_doc/
  10. J.-Y. Park, "Experiments on vision guided docking of an autonomous underwater vehicle using one camera", Ocean Engineering, Vol. 36, No. 1, pp. 48-e61, 2009. DOI: http://dx.doi.org/10.1016/j.oceaneng.2008.10.001 https://doi.org/10.1016/j.oceaneng.2008.10.001
  11. Gyumin Lee, et al, "New algorithm of localization Using Odometry and RFID system", Journal of CICS, Vol. 2008, No. 10, pp. 91-92, 2008.