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JRM Vol.22 No.1 pp. 28-35
doi: 10.20965/jrm.2010.p0028
(2010)

Paper:

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Human Following by an Omnidirectional Mobile Robot Using Maps Built from Laser Range-Finder Measurement

Takashi Ogino*, Masahiro Tomono**, Toshinari Akimoto***,
and Akihiro Matsumoto***

*Omori Machinery Co., Ltd., 2761 Nishikata, Koshigaya, Saitama, Japan

**Future Robotics Technology Center, Chiba Institute of Technology, 2-17-1 Tsudanuma Narashino, Chiba 275-0016, Japan

***Dept. of System Robotics, Toyo University, 2100 Kujirai, Kawagoe, Saitama 350-8585, Japan

Received:
February 6, 2009
Accepted:
January 1, 1970
Published:
February 20, 2010
Creative Commons License
Keywords:
omnidirectional mobile robot, human tracking, scan matching, map building, localization
Abstract
This paper deals with map building from laser range finder measurement in an unknown indoor environment and its application to human following by an omnidirectional mobile robot. After reviewing basic strategies of human following by a mobile robot involving simultaneous acquisition of indoor map and robot location acquisition, we implemented “pseudo” odometry, rather than conventional odometry, for the omnidirectional mobile robot, using this information to improve scan-matching calculation accuracy. We then conducted experiments in which the robot followed a pedestrian. We confirmed that the robot could follow different pedestrian trajectories if walking was slow, and that our approach effectively improved scan matching calculation accuracy.
Cite this article as:
T. Ogino, M. Tomono, T. Akimoto, and A. Matsumoto, “Human Following by an Omnidirectional Mobile Robot Using Maps Built from Laser Range-Finder Measurement,” J. Robot. Mechatron., Vol.22 No.1, pp. 28-35, 2010.
Data files:
References
  1. [1] D. Fox, S. Thrun, W. Burgard, and F. Dellaert, “Particle filters for mobile robot localization,” in A. Doucet, N. Freitas, and N. Gordon, ed., Sequential Monte Carlo Methods in Practice, New York: Springer-Verlag, 2000.
  2. [2] F. Lu and E. Milios, “Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans,” Proc. of IEEE Comp. Soc. Cong. on Computer Vision and Pattern Recognition, pp. 935-938, 1994.
  3. [3] S. Thrun, “Robotic Mapping: A Survey,” in G. Lakemeyer and B. Nebel, ed., Exploring Artificial Intelligence in the New Millennium, Morgan Kaufmann, 2002.
  4. [4] K. Oikawa, H. Takauji, T. Emaru, S. Okubo, and T. Tsuchiya, “Navigation using Local Landmarks in a Corridor Environment,” J. of Robotics and Mechatronics, Vol.17, No.3, pp. 262-268, 2005.
  5. [5] Y. Nagumo and A. Ohya, “Human following behavior of an autonomous mobile robot using light-emitting device,” Proc. JSME Robotics and Mechatronics Conference 2001, 2P1-H6, 2001 (in Japanese).
  6. [6] T. Itoh and H. Miyata, “Infrared light tracing approach to autonomous mobile robot for human following behavior,” JSME Design & Systems Conf. 2003, pp. 279-280, 2003 (in Japanese).
  7. [7] D. Gavrila, “The Visual Analysis of Human Movement: A Survey,” Computer Vision and Image Understanding, Vol.73, No.1, pp. 82-98, 1999.
  8. [8] H. Nakano, K. Shimowaki, and T. Yamanaka, “Person Following System for the Autonomous Mobile Robot by Independent Tracking of Left and Right Feet,” J. of the Robotics Society of Japan, Vol.25, No.8, pp. 707-716, 2007 (in Japanese).
  9. [9] D. Schulz, W. Burgard, D. Fox, and A. B. Cremers, “People Tracking with a Mobile Robot Using Sample-based Joint Probabilistic Data Association Filters,” Int. J. of Robotics Research, Vol.22, No.2, pp. 99-116, 2003.
  10. [10] M. Montemerlo, S. Thrun, and W. Whittaker, “Conditional particle filters for simultaneous mobile robot localization and peopletracking,” Proc. of IEEE Int. Conf. on Robotics and Automation (ICRA), 2002.
  11. [11] S. Okusako and S. Sakane, “Human Tracking with a Mobile Robot using a Laser Rage-Finder,” J. of the Robotics Society of Japan, Vol.24, No.5, pp. 605-613, 2006 (in Japanese).
  12. [12] K. Tanaka and E. Kondo, “Towards Real-Time Global Localization in Dynamic Unstructured Environments,” JSME Int. J. Series C, Vol.49, Nol.3, pp. 905-911, 2006.
  13. [13] A. Matsumoto, S. Tsukuda, and G. Yoshita, “Navigation of an omnidirectional mobile robot by teaching a few omnidirectional images,” J. of Robotics and Mechatronics, Vol.16, No.1, pp. 80-89, 2004.
  14. [14] A. Ishioka, M. Tomono, T. Tsubouchi, and S. Yuta, “Probablistic Localization and Mapping by Mobile Robot with Fusing Odometry and Estimated Motion from Scan Matched LRF Data,” Proc. JSME Robotics and Mechatronics Conf. 2004, 1P1-L1-74, 2004 (in Japanese).
  15. [15] P. J. Besl and N. D. Mckay, “A Method for Registration of 3-D Shapes,” IEEE Trans. on PAMI, Vol.14, No.2, pp. 239-256, 1992.

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