DOI QR코드

DOI QR Code

Evaluation of Robot Vision Control Scheme Based on EKF Method for Slender Bar Placement in the Appearance of Obstacles

장애물 출현 시 얇은 막대 배치작업에 대한 EKF 방법을 이용한 로봇 비젼제어기법 평가

  • Hong, Sung-Mun (Department of Mechanical Engineering, Chosun University) ;
  • Jang, Wan-Shik (Department of Mechanical Engineering, Chosun University) ;
  • Kim, Jae-Meung (Department of Mechanical Engineering, Chosun University)
  • 홍성문 (조선대학교 기계공학과) ;
  • 장완식 (조선대학교 기계공학과) ;
  • 김재명 (조선대학교 기계공학과)
  • Received : 2015.01.22
  • Accepted : 2015.04.28
  • Published : 2015.05.01

Abstract

This paper presents the robot vision control schemes using Extended Kalman Filter (EKF) method for the slender bar placement in the appearance of obstacles during robot movement. The vision system model used for this study involves the six camera parameters($C_1{\sim}C_6$). In order to develop the robot vision control scheme, first, the six parameters are estimated. Then, based on the estimated parameters, the robot's joint angles are estimated for the slender bar placement. Especially, robot trajectory caused by obstacles is divided into three obstacle regions, which are beginning region, middle region and near target region. Finally, the effects of number of obstacles using the proposed robot's vision control schemes are investigated in each obstacle region by performing experiments of the slender bar placement.

Keywords

References

  1. Kim, K. K., Kang, S. S., Kim, J. B., Lee, J. Y., Do, H. M., et al., "Object Recognition Method for Industrial Intelligent Robot," J. Korean Soc. Precis. Eng., Vol. 30, No. 9, pp. 901-908, 2013. https://doi.org/10.7736/KSPE.2013.30.9.901
  2. Tsai, R. Y., "Synopsis of Recent Progress on Camera Calibration for 3D Machine Vision," MIT Press, pp. 146-159, 1989.
  3. Beardsley, P. A., Zisserman, A., and Murray, D. W., "Sequential Updating of Projective and Affine Structure from Motion," International Journal of Computer Vision, Vol. 23, No. 3, pp. 235-259, 1997. https://doi.org/10.1023/A:1007923216416
  4. Berthold, K. P. H., "Robot Vision," MIT Press, pp. 46-48, 1986.
  5. Sandon, P. A., "Control of Eye and Arm Movements Using Active, Attentional Vision," International Journal of Pattern Recognition and Artificial Intelligence, Vol. 8, No. 6, pp. 1471-1491, 1994. https://doi.org/10.1142/S0218001494000711
  6. Lippiello, V., Siciliano, B., and Villani, L., "Adaptive Extended Kalman Filtering for Visual Motion Estimation of 3D Objects," Control Engineering Practice, Vol. 15, No. 1, pp. 123-134, 2007. https://doi.org/10.1016/j.conengprac.2006.05.006
  7. Chen, G., Xia, Z., Ming, X., Lining, S., Ji, J., et al., "Camera Calibration based on Extended Kalman Filter using Robot's Arm Motion," Proc. of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 1839-1844, 2009.
  8. Chen, L., Hu, H., and McDonald-Maier, K., "Ekf Based Mobile Robot Localization," Proc. of the IEEE 3rd International Conference on Emerging Security Technologies, pp. 149-154, 2013.
  9. Ahmad, H. and Namerikawa, T., "Extended Kalman Filter-Based Mobile Robot Localization with Intermittent Measurements," Systems Science & Control Engineering: An Open Access Journal, Vol. 1, No. 1, pp. 113-126, 2013. https://doi.org/10.1080/21642583.2013.864249
  10. Parnian, N. and Golnaraghi, F., "Integration of a Multi-Camera Vision System and Strapdown Inertial Navigation System (SDINS) with a Modified Kalman Filter," Sensors, Vol. 10, No. 6, pp. 5378-5394, 2010. https://doi.org/10.3390/s100605378
  11. Zhou, S., Fei, F., Zhang, G., Liu, Y., and Li, W. J., "Hand-Writing Motion Tracking with Vision-Inertial Sensor Fusion: Calibration and Error Correction," Sensors, Vol. 14, No. 9, pp. 15641-15657, 2014. https://doi.org/10.3390/s140915641
  12. Hong, S. M., "Development of Robot Vision Control Schemes using the N-R and EKF Methods for the Moving Target Tracking and Slender Bar Placement Tasks," M.Sc. Thesis, Engineering, School of Mechanical Engineering, Chosun University, 2015.
  13. Jang, W., Kim, K., Kim, K., and Ahn, H., "An Experimental Study on the Optimal Number of Cameras used for Vision Control System," Journal of the Korean Society of Manufacturing Technology Engineers, Vol. 13, No. 2, pp. 94-103, 2004.
  14. David, F., Robert, P., and Roger, P., "Statistic," W. W. Norton, pp.58-59, 1978.