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JRM Vol.26 No.1 pp. 68-77
doi: 10.20965/jrm.2014.p0068
(2014)

Paper:

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Development of Mobile Robot System Equipped with Camera and Laser Range Finder Realizing HOG-Based Person Following and Autonomous Returning

Masashi Awai*, Atsushi Yamashita**, Takahito Shimizu*,
Toru Kaneko*, Yuichi Kobayashi*, and HajimeAsama**

*Department of Mechanical Engineering, Shizuoka University, 3-5-1 Johoku, Naka-ku, Hamamatsu-shi, Shizuoka 432-8561, Japan

**Department of Precision Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Received:
September 10, 2013
Accepted:
November 7, 2013
Published:
February 20, 2014
Creative Commons License
Keywords:
mobile robot, laser range finder, camera, person following
Abstract
In this paper, we propose a mobile robot system which has functions of person following and autonomous returning. The robot realizes these functions by analyzing information obtained with camera and laser range finder. Person following is performed by using HOG features, color information, and pattern of range data. Along with person following, a map of the ambient environment is generated from range data. Autonomous returning to the starting point is performed by applying potential method to the generated map. We verified the proposed method by experiment using a wheel mobile robot in an indoor environment.
Cite this article as:
M. Awai, A. Yamashita, T. Shimizu, T. Kaneko, Y. Kobayashi, and HajimeAsama, “Development of Mobile Robot System Equipped with Camera and Laser Range Finder Realizing HOG-Based Person Following and Autonomous Returning,” J. Robot. Mechatron., Vol.26 No.1, pp. 68-77, 2014.
Data files:
References
  1. [1] M. Misawa, T. Yoshida, and S. Yuta, “A Smart Handcart with Autonomous Returning Function,” J. of Robotics Society of Japan, Vol.25, No.8, pp. 1199-1206, 2007 (in Japanese).
  2. [2] T. Lixin and S. Yuta, “Mobile Robot Playback Navigation Based on Robot Pose Calculation Using Memorized Omnidirectional Images,” J. of Robotics and Mechatronics, Vol.14, No.4, pp. 366-374, 2002.
  3. [3] N. Tsuda, S. Harimoto, T. Saitoh, and R. Konishi, “Mobile Robot with Following and Returning Mode,” Proc. of the 18th IEEE Int. Symposium on Robot and Human Interactive Communication (ROMAN2009), ThB1.3, pp. 933-938, 2009.
  4. [4] T. Shimizu, M. Awai, A. Yamashita, and T. Kaneko, “Mobile Robot System Realizing Human Following and Autonomous Returning Using Laser Range Finder and Camera,” Proc. of the 18th Korea-Japan JointWorkshop on Frontiers of Computer Vision (FCV2012), 2012.
  5. [5] S. Okusako and S. Sakane, “Human Tracking with a Mobile Robot using a Laser Range-Finder,” J. of Robotics Society of Japan, Vol.24, No.5, pp. 605-613, 2006 (in Japanese).
  6. [6] J. Satake and J. Miura, “Person Following of a Mobile Robot using Stereo Vision,” J. of Robotics Society of Japan, Vol.28, No.9, pp. 1091-1099, 2010 (in Japanese).
  7. [7] M. Saito, K. Yamazaki, N. Hatao, R. Hanai, K. Okada, and M. Inaba, “Pedestrian Detection using a LRF and a Small Omni-view Camera for Outdoor Personal Mobility Robot,” Proc. of the 2010 IEEE Int. Conf. on Robotics and Biomimetics (ROBIO 2010), pp. 196-201, 2010.
  8. [8] M. Isard and A. Blake, “Condensation-conditional density propagation for visual tracking,” Int. J. of Computer Vision, Vol.29, No.1, pp. 5-28, 1998.
  9. [9] R. E. Schapire and Y. Singer, “Improved boosting algorithms using confidence rated predictions,” Machine Learning, No.37, pp. 297-336, 1999.
  10. [10] N. Dalal and B. Triggs, “Histograms of Oriented Gradients for Human Detection,” Proc. of the 2005 IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR2005), pp. 886-893, 2005.
  11. [11] H. Takahashi, K. Nakamura, H. Zhao, and R. Shibasaki, “Human Identification Using Laser Scanners and Image Sensors,” Proc. of Asian Conf. on Remote Sensing 2007, TS24-2, 2007.
  12. [12] T. Kailath, “The Divergence and Bhattacharyya Distance Measures in Signal Selection,” IEEE Trans. on Communication Technology, Vol.COM-15, No.1, pp. 52-60, 1967.
  13. [13] P. J. Besl and N. D. Mckay, “A Method for Registration of 3-D Shapes,” IEEE Trans. on Pattern Analysis andMachine Intelligence, Vol.14, No.2, pp. 239-256, 1992.
  14. [14] S. Iwashina, A. Yamashita, and T. Kaneko, “3-D Map Building in Dynamic Environments by a Mobile Robot Equipped with Two Laser Range Finders,” Proc. of the 3rd Asia Int. Symposium on Mechatronics, TP1-3(1), pp. 1-5, 2008.
  15. [15] K. Sato, “Deadlock-free Motion Planning Using the Laplace Potential Field,” Proc. of the Joint Int. Conf. on Mathematical Methods and Supercomputing in Nuclear Applications, pp. 449-461, 1994.
  16. [16]

    Supporting Online Materials:[a] Daimler Pedestrian Classification Benchmark Dataset,
    http://www.gavrila.net/Datasets/datasets.html

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Last updated on Apr. 22, 2024