Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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A Real-time and Off-line Localization Algorithm for an Inpipe Robot by Detecting Elbows

엘보 인식에 의한 배관로봇의 실시간 위치 추정 및 후처리 위치 측정 알고리즘

  • Lee, Chae Hyeuk (Department of Mechanical Engineering, Kyung Hee University) ;
  • Kim, Gwang Ho (Department of Mechanical Engineering, Kyung Hee University) ;
  • Kim, Jae Jun (Department of Mechanical Engineering, Kyung Hee University) ;
  • Kim, Byung Soo (Department of Mechanical Engineering, Kyung Hee University) ;
  • Lee, Soon Geul (Department of Mechanical Engineering, Kyung Hee University)
  • Received : 2013.12.05
  • Accepted : 2014.08.27
  • Published : 2014.10.01
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Abstract

Robots used for pipe inspection have been studied for a long time and many mobile mechanisms have been proposed to achieve inspection tasks within pipelines. Localization is an important factor for an inpipe robot to perform successful autonomous operation. However, sensors such as GPS and beacons cannot be used because of the unique characteristics of inpipe conditions. In this paper, an inpipe localization algorithm based on elbow detection is presented. By processing the projected marker images of laser pointers and the attitude and heading data from an IMU, the odometer module of the robot determines whether the robot is within a straight pipe or an elbow and minimizes the integration error in the orientation. In addition, an off-line positioning algorithm has been performed with forward and backward estimation and Procrustes analysis. The experimental environment has consisted of several straight pipes and elbows, and a map of the pipeline has been constructed as the result.

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References

  1. S. G. Gon and H. R. Choi, "Automated technology for pipeline inspection using inpipe robot," Journal of Korean Society of Nondestructive Testing, vol. 22, no. 3, 2002.
  2. X. Li and S. S. Iyengar, "On optimizing autonomous pipeline inspection," Transactions on Robotics, vol. 28, no. 1, 2012.
  3. A. Ahrary and M. Ishikawa, "A laser scanner for landmark detection with the sewer inspection robot KANTARO," Proc. of the 2006 IEEE/SMC International Conference on System of Systems Engineering, 2006.
  4. S. S. Park and Y. W. Rho, "Development of the odometry system for the intelligent PIG," Conference of Korean Society of Mechanical Engineering, pp. 222-227, 2001.
  5. D. J. Hyun and H. S. Yang, "Dead-reckoning sensor system and tracking algorithm for 3-d pipeline mapping," Mechatronics, vol. 20, no. 2, pp. 213-223, 2010. https://doi.org/10.1016/j.mechatronics.2009.11.009
  6. T. Viklands, "Algorithms for the weighted orthogonal procrustes problem and other least squares problems," Ph.D. dissertation, Dept. Comput. Sci., Umea University, Umea, Sweden, 2006.
  7. Alex Townsend. (2011, Aug.). Procrustes Shape Analysis [Online], Available: http://www.chebfun.org
  8. J. Yu, J. G. Lee, and C. G. Park, "An off-line navigation of a geometry PIG using a modified nonlinear fixed-interval smoothing filter," Control Engineering Practice, vol. 13, no. 11, pp. 1403-1411, 2005. https://doi.org/10.1016/j.conengprac.2004.12.016
  9. P. V. Unnikrishnan, B. Thornton, T. Ura, and Y. Nose, "A conical laser light-sectioning method for navigation of autonomous underwater vehicles for internal inspection of pipelines," OCEANS '09, pp. 1-9, 2009.
  10. M. Kolesnik, "Visual orientation in the sewer - adaptation to the environment," International Conference on Pattern Recognition, vol. 16, no. 2, pp. 856-859, 2002.
  11. S. G. Roh, D. W. Kim, J. S. Lee, H. P. Moon, and H. R. Choi, "In-pipe robot based on selective drive mechanism," International Journal of Control, Automation and Systems, vol. 7, no. 1, pp. 105-112, 2009. https://doi.org/10.1007/s12555-009-0113-z