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

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Predictive Control of an Efficient Human Following Robot Using Kinect Sensor

Kinect 센서를 이용한 효율적인 사람 추종 로봇의 예측 제어

  • Heo, Shin-Nyeong (Department of Interdisciplinary Program in Robotics, Pusan National University) ;
  • Lee, Jang-Myung (Department of Electrical Engineering, Pusan National University)
  • Received : 2014.02.02
  • Accepted : 2014.06.09
  • Published : 2014.09.01
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Abstract

This paper proposes a predictive control for an efficient human following robot using Kinect sensor. Especially, this research is focused on detecting of foot-end-point and foot-vector instead of human body which can be occluded easily by the obstacles. Recognition of the foot-end-point by the Kinect sensor is reliable since the two feet images can be utilized, which increases the detection possibility of the human motion. Depth image features and a decision tree have been utilized to estimate the foot end-point precisely. A tracking point average algorithm is also adopted in this research to estimate the location of foot accurately. Using the continuous locations of foot, the human motion trajectory is estimated to guide the mobile robot along a smooth path to the human. It is verified through the experiments that detecting foot-end-point is more reliable and efficient than detecting the human body. Finally, the tracking performance of the mobile robot is demonstrated with a human motion along an 'L' shape course.

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References

  1. T.-S. Jin and J.-M. Lee, "Object position estimation and optimal moving planning of mobile manipulator based on active camera," The Transactions of the Korean Institute of Electrical Engineers, vol. 42, no. 5, pp. 1-12, Sep. 2005.
  2. N.-Y. Ko, D.-J. Seo, and Y.-S. Moon, "A method for real time target following of a mobile robot using heading and distance information," Journal of Korean Institute of Intelligent Systems, vol. 18, no. 5, pp. 624-631, 2008. https://doi.org/10.5391/JKIIS.2008.18.5.624
  3. B.-S. Choi and J.-M. Lee, "A capturing algorithm of moving object using single curvature trajectory," Journal of Control, Automation, and Systems Engineering (in Korean), vol. 12, no. 2, Feb. 2006. https://doi.org/10.5302/J.ICROS.2006.12.2.145
  4. Microsoft Research Kinect for Windows SDK Programming guide
  5. G. Bradski, The OpenCV Library. Dr. Dobb's Journal of Software Tools, 2000.
  6. V. Ganapathi, C. Plagemann, D. Koller, and S. Thrun, "Real time motion capture using a single time-of-flight camera," Proc. of CVPR, pp. 755-762, 2010.
  7. Y. Amit and D. Geman, "Shape quantization and recognition with randomized trees," Neural Computation, vol. 9, no. 7, pp. 1545-1588, 1997. https://doi.org/10.1162/neco.1997.9.7.1545
  8. G. Mori and J. Malik, "Recovering 3D human body configurations using shape contexts," Pattern Analysis and Machine Intelligence, vol. 28, no. 7, pp. 1052-1062, Jul. 2006. https://doi.org/10.1109/TPAMI.2006.149
  9. C. Plagemann, V. Ganapathi, D. Koller, and S. Thrun, "Real-time identification and localization of body parts from depth images," In Proc. ICRA, pp. 3108-3113, 2010.
  10. C. Bregler and J. Malik, "Tracking people with twists and exponential maps," Proc. of CVPR, pp. 8-15, 1998.
  11. A. Carballo, A. Ohya, and S. Yuta, "Fusion of double layered multiple laser range finders for people detection from a mobile robot," Proc. of IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, pp. 677-682, 2008.
  12. C. Barron and I. A. Kakadiaris, "Estimating anthropometry and pose from a single image," Proc. of CVPR, pp. 1669-1676, 2000.
  13. D. Comaniciu and P. Meer, "Mean shift: A robust approach toward feature space analysis," IEEE Trans. PAMI, vol. 24, no. 5, 2002.
  14. J. Shotton, A. Fitzgibbon, M. Cook, T. Sahrp, M. Finocchio, R. Moore, A. Kipman, and A. Blake, "Real-time human pose recognition in parts from signle depth images," Proc. of CVPR, pp. 1297-1304, 2011.
  15. D. Ramanan and D. A. Forsyth, "Finding and tracking people from the bottom up," In CVPR (2), pp. 467-474, 2003.
  16. P. A. Viola and M. J. Jones, "Rapid object detection using a boosted cascade of simple features," Proc. of CVPR (1), pp. 511-518, 2001.
  17. P. Udsatid, N. Niparnan, and A. Sudsang, "Human position tracking for side by side walking mobile robot using foot positions," Proc. of the 2012 IEEE International Conference on Robotics and Biomimetics, pp. 1374-1378, Dec. 2012.