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JRM Vol.23 No.1 pp. 163-172
doi: 10.20965/jrm.2011.p0163
(2011)

Paper:

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Target Person Identification and Following Based on Omnidirectional Camera and LRF Sensor Fusion from a Moving Robot

Mehrez Kristou, Akihisa Ohya, and Shin’ichi Yuta

Intelligent Robot Laboratory, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan

Received:
July 21, 2010
Accepted:
October 17, 2010
Published:
February 20, 2011
Creative Commons License
Keywords:
people detection, human tracking, human following, target person identification
Abstract
In this paper, we introduce an approach to identify and follow a target person for a service robot application. The robot is equipped with LRF and omnidirectional camera. Our approach is based on multisensor fusion in which a person is identified using the panoramic image and tracked using the Laser Range Finder (LRF). A target person selection is implemented to improve the identification when multiple candidates are detected. Our approach is successfully implemented on a mobile robot. A simplified target person following behavior is implemented to focus on the proposed method’s efficiency. Several experiments are conducted and showed the effectiveness of our approach to identify and follow human in indoor environments.
Cite this article as:
M. Kristou, A. Ohya, and S. Yuta, “Target Person Identification and Following Based on Omnidirectional Camera and LRF Sensor Fusion from a Moving Robot,” J. Robot. Mechatron., Vol.23 No.1, pp. 163-172, 2011.
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References
  1. [1] M. Hans, B. Graf, and R. Schraft, “Robotic home assistant care-obot: Past - present - future,” in In IEEE Int.Workshop on Robot and Human interactive Communication (ROMAN2002), pp. 380-385, 2002.
  2. [2] W. Burgard, P. Trahanias, D. Hähnel, M. Moors, D. Schulz, H. Baltzakis, and A. Argyros, “Tourbot and webfair: Web-operated mobile robots for tele-presence in populated exhibitions,” in Proc. IROS Workshop Robots Exhib., pp. 1-10, 2002.
  3. [3] M. Bennewitz, F. Faber, D. Joho, M. Schreiber, and S. Behnke, “Towards a humanoid museum guide robot that interacts with multiple persons,” in in Proc. of the IEEE/RSJ Int. Conf. on Humanoid Robots (Humanoids), 2005.
  4. [4] W. Burgard, A. B. Cremers, D. Fox, D. Hähnel, G. Lakemeyer, D. Schulz, W. Steiner, and S. Thrun, “Experiences with an interactive museum tour-guide robot,” Artif. Intell., Vol.114, No.1-2, pp. 3-55, 1999.
  5. [5] A. Treptow, G. Cielniak, and T. Duckett, “Active people recognition using thermal and grey images on a mobile security robot,” pp. 2103-2108, Aug. 2005.
  6. [6] A. Fod, A. Howard, and M. J. Matarić, “Laser-based people tracking,” in IEEE Int. Conf. on Robotics and Automation (ICRA), Washington D.C., pp. 3024-3029, May 2002.
  7. [7] M. Montemerlo, S. Thrun, and W. Whittaker, “Conditional particle filters for simultaneous mobile robot localization and peopletracking,” in IEEE Int. Conf. on Robotics and Automation (ICRA), Washington, D.C., pp. 695-701, May 2002.
  8. [8] H. Zhao, Y. Chen, X. Shao, K. Katabira, and R. Shibasaki, “Monitoring a populated environment using single-row laser range scanners from a mobile platform,” in IEEE Int. Conf. on Robotics and Automation (ICRA), Roma, Italy, pp. 4739-4745, April 2007.
  9. [9] K. O. Arras, Ó. Martínez Mozos, and W. Burgard, “Using boosted features for the detection of people in 2d range data,” in IEEE Int. Conf. on Robotics and Automation (ICRA), Roma, Italy, pp. 3402-3407, April 2007.
  10. [10] N. Ogale, “A survey of techniques for human detection from video,” Master’s thesis, University of Maryland, 2006.
  11. [11] C. Schlegel, J. Illmann, H. Jaberg, M. Schuster, and R. Wörz, “Vision based person tracking with a mobile robot,” in Proc. 9th British Machine Vision Conf., pp. 418-427, 1998.
  12. [12] Y. Nakauchi and R. Simmons, “Social behavioral robot that stands in line,” in Proc. of the IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC), Tokyo, Japan, pp. 993-998, October 1999.
  13. [13] D. Beymer and K. Konolige, “Tracking people from a mobile platform,” in Proc. of the Int. Joint Conf. on Artificial Intelligence, 2001.
  14. [14] S. Bahadori, G. Grisetti, L. Iocchi, R. Leone, and D. Nardi, “Realtime tracking of multiple people through stereo vision,” in Proc. of IEE Int. Workshop on Intelligent Environments, 2005.
  15. [15] H. Noguchi, T. Mori, T. Matsumoto, M. Shimosaka, and T. Sato, “Multiple-person tracking by multiple cameras and laser range scanners in indoor environments,” J, of Robotics and Mechatronics, Vol.22, No.2, pp. 221-229, April 2010.
  16. [16] R. Mu noz-Salinas, E. Aguirre, and M. García-Silvente, “People detection and tracking using stereo vision and color,” Image Vision Comput., Vol.25, No.6, pp. 995-1007, 2007.
  17. [17] N. Bellotto and H. Hu, “Multisensor-based human detection and tracking for mobile service robots,” IEEE Trans. on Systems, Man, and Cybernetics – Part B, Vol.39, No.1, pp. 167-181, 2009.
  18. [18] M. Kobilarov, M. Hyams, P. Batavi, and G. Sukhatme, “People tracking and following with mobile robot using an omnidirectional camera and a laser,” in IEEE Int. Conf. on Robotics and Automation, pp. 557-562, 2006.
  19. [19] Z. Zivkovic and B. Kröse, “Part based people detection using 2d range data and images,” in IEEE Int. Conf. on Intelligent Robots and Systems (IROS), San Diego CA, pp. 214-219, October 2007.
  20. [20] J. Blanco, W. Burgard, R. Sanz, and J. Fernandez, “Fast face detection for mobile robots by integrating laser range data with vision,” in Proc. of the Int. Conf. on Advanced Robotics (ICAR), 2003.
  21. [21] S. Feyrer and A. Zell, “Robust real-time pursuit of persons with a mobile robot using multisensor fusion,” in 6th Int. Conf. on Intelligent Autonomous Systems (IAS-6), Venice, Italy, pp. 710-715, 2000.
  22. [22] M. Kleinehagenbrock, S. Lang, J. Fritsch, F. Lömker, G. A. Fink, and G. Sagerer, “Person tracking with a mobile robot based on multi-modal anchoring,” in Proc. IEEE Int.Workshop on Robot and Human Interactive Communication (ROMAN), Berlin, Germany: IEEE, pp. 423-429, September 2002.
  23. [23] G. Cserey, J. McRaven, and M. Scheutz, “Fast, reliable, adaptive, bimodal people tracking for indoor environments,” in Int. Conf. on Intelligent Robots and Systems, pp. 1347-1352, 2004.
  24. [24] G. Cielniak and T. Duckett, “People recognition by mobile robots,” J. Intell. Fuzzy Syst., Vol.15, No.1, pp. 21-27, 2004.
  25. [25] S. Baker and S. K. Nayar, “Single viewpoint catadioptric cameras,” in Panoramic Vision: Sensors, Theory, Applications, R. Benosman and S. B. Kang (eds.), Springer-Verlag, 2001.
  26. [26] P. Viola and M. Jones, “Rapid object detection using a boosted cascade of simple features,” in Proc. of IEEE Conference on Computer Vision and Pattern Recognition, December 2001.
  27. [27] N. Bellotto and H. Hu, “People tracking and identification with a mobile robot,” in Proc. of the IEEE Int. Conf. on Mechatronics and Automation (ICMA 2007), Harbin, China, pp. 3565-3570, August 2007.
  28. [28] G. Bradski and A. Kaehler, “Learning OpenCV: Computer Vision with the OpenCV Library,” O’Reilly Media, September 2008.
    ISBN: 978-0-596516134
  29. [29] M. Kristou, A. Ohya, and S. Yuta, “Panoramic vision and lrf sensor fusion based human identification and tracking for autonomous luggage cart,” in Robot and Human Interactive Communication, 2009, RO-MAN 2009, The 18th IEEE Int. Symposium on, pp. 711-716, 2009.
  30. [30] H. Kawata, A. Ohya, S. Yuta, W. Santosh, and T. Mori, “Development of ultra-small lightweight optical range sensor system,” in IEEE Int. Conf. on Intelligent Robots and Systems (IROS), pp. 3277-3282, 2005.

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