JRM Vol.24 No.6 pp. 1071-1079
doi: 10.20965/jrm.2012.p1071


The Effect of Mobile Robot on Group Behavior of Animal

Daisuke Fujiwara*1, Kojiro Iizuka*2, Yoshiyuki Matsumura*3,
Tohru Moriyama*4, Ryo Watanabe*1, Koichiro Enomoto*5,
Masashi Toda*6, and Yukio Gunji*7

*1Graduate School of Science and Technology, Shinshu University, 3-15-1 Tokida, Ueda City 386-8567, Japan

*2International Young Researchers Empowerment Center, Shinshu University, 3-15-1 Tokida, Ueda City 386-8567, Japan

*3Division of Textile and Kansei Engineering, Faculty of Textile Science and Technology, Shinshu University, 3-15-1 Tokida, Ueda City 386-8567, Japan

*4Division of Mechanical Engineering and Robotics, Faculty of Textile Science and Technology, Shinshu University, 3-15-1 Tokida, Ueda City 386-8567, Japan

*5Graduate School of Systems Information Science, Future University Hakodate, 116-2 Kamedanakano-cho, Hakodate, Hokkaido 041-8655, Japan

*6Department of Center for Multimedia and Information Technologies, Kumamoto University, 2-39-1 Kurokami, Kumamoto 860-8555, Japan

*7Department of Earth & Planetary Sciences, Faculty of Science, Kobe University, 1-1 Rokko-dai, Nada, Kobe 657-8501, Japan

October 6, 2011
October 22, 2012
December 20, 2012
soldier crab, animal-robot interaction, robotics science
This paper observes the effect of a mobile robot on the group behavior of soldier crabs. The mobile robot interacts with eight soldier crabs. For the experimental analysis, this paper adopts four settings. In the first setting, eight soldier crabs are placed in an experiment area without the presence of the robot. In the second, third, and fourth settings, eight soldier crabs are placed in an experiment area with, respectively, a stationary robot, a continuously moving robot, and an intermittently moving robot. These experimental results are analyzed using a fluctuation index. From analysis, it was found that the fluctuation slope for the fourth experiment alone differs from that for other experiments. This result suggests that the intermittently moving robot influences the group behavior of soldier crabs.
Cite this article as:
D. Fujiwara, K. Iizuka, Y. Matsumura, T. Moriyama, R. Watanabe, K. Enomoto, M. Toda, and Y. Gunji, “The Effect of Mobile Robot on Group Behavior of Animal,” J. Robot. Mechatron., Vol.24 No.6, pp. 1071-1079, 2012.
Data files:
  1. [1] J. Halloy et al., “Social Integration of Robots into Groups of Cockroaches to Control Self-Organized Choices,” Science, Vol.318, No.5853, pp. 1155-1158, 2007.
  2. [2] A. Gribovskiy, J. Halloy, J. Deneubourg, H. Bleuler, and F. Mondada, “Towards Mixed Societies of Chickens and Robots,” Proc. The 2010 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS 2010), pp. 4722-4728, 2010.
  3. [3] R. S. Guerra, H. Aonuma, K. Hosoda, and M. Asada, “Behavior Change of Crickets in a Robot-Mixed Society,” J. of Robotics and Mechatronics, Vol.22, No.4, 2010.
  4. [4] F. A. McNeill, “Studies in Austrailan carcinology, A revision of the family Mictrydae,” Records of the Australian Museum, No.2, Vol.5, pp. 100-128, 1926.
  5. [5] M. Takeda, “Soldier crab from Australia and Japan,” Bulletin of the National Science Museum. Series A, Zoology, Vol.4, pp. 31-38, 1978.
  6. [6] S. Dittmann, “Impact of foraging soldier crabs (Decapoda: Mictyridae) on meiofauna in a tropical tidal flat,” Rec. revisata de biologia toropical, Vol.41, pp. 627-637, 1993.
  7. [7] Y. Nakasone and T. Akamine, “The reproductive cycle and young crab’s growth of the soldier crab Mictyris brevidactylus Stimpson,” Biological Magazine Okinawa, Vol.19, pp. 17-23, 1981 (in Japanese).
  8. [8] T. Yamaguchi, “A preliminary report on the ecology of the sand bubbler crab,” Mictyris longicarpus Latreille, Benthos Research Vol.11-12, pp. 1-13, 1976 (in Japanese).
  9. [9] S. Takeda and M. Murai, “Microhabitat use by the soldier crab Mictyris brevidactylus (Brachyura Mictyridae) interchangeability of surface and subsurface feeding through burrow structure alteration,” J. of Crustacean Biology, Vol.24, pp. 327-339, 2004.
  10. [10] J. K. Parrish and L. Edelstein-Keshet, “Complexity pattern and evolutionary trade-offs in animal aggregation,” Science, Vol.284, pp. 99-101, 1999.
  11. [11] M. Ballerini et al., “Empirical investigation of starling flocks: a benchmark study in collective animal behavior,” Animal Behavior, Vol.76, pp. 201-215, 2008.
  12. [12] Y. Gunji et al., “Robust Swarm Model Based on Mutual Anticipation: Swarm as a Mobile Network Analyzed by Rough Set Lattice,” Int. J. of Artificial Life Research, Vol.3, No.1, pp. 45-58, 2012.
  13. [13] H. O. Nalbach, “Discontinuous turning reaction during escape in Soldier Crabs,” The J. of Experimental Biology, Vol.148, pp. 482-487, 1990.
  14. [14] H. O. Nalbach, G. Nalbach, and L. Forzin, “Visual control eyestalk orientation in crabs: vertical optokinetics, visual fixation of the horizon, and eye design,” J. of Comparative Physiology A, Vol.165, pp. 577-587, 1989.
  15. [15] S. Cannicci, L. Morino, and M. Vannini, “Behavioural evidence for visual recognition of predators by the mangrove climbing crab Sesarma Leptosoma,” Animal Behaviour, Vol.63, pp. 77-83, 2002.
  16. [16] P.Castro, P. J. F. Davie, P. K. L. Ng, andB. R. de Forges, “Studies on brachyuran: a Homage to Daniele Guinot,” BRILL, Vol.11, 2010.
  17. [17] S. Takeda, “Sexual differences in behaviour during the breeding season in the soldier crab (Mictyris brevidactylus),” J. of Zoology, Vol.266, pp. 197-204, 2005.
  18. [18] K. Imai and I. Imai, “Computational geometry,” Kyoritsu Shuppan Co., Ltd., 1994 (in Japanese).
  19. [19] T. Mushya, “Idea of fluctuation,” NHK Publishing Co., Ltd., 1998 (in Japanese).
  20. [20] W. Matsunaga and E. Watanabe, “Visual motion with pink noise induces predation behavior,” Scientific Reports 2, Article number 219, 2011.
  21. [21] N. Aoyagi, Z. R. Struzik, K. Kiyono, and Y. Yamamoto, “Autonomic Imbalance induced breakdown of long-range dependence in healthy heat rate,” Methods of Information in Medicine, Vol.46, pp. 174-178, 2007.
  22. [22] F. Beckers, B. Verheyden, and A. E. Aubert, “Aging and nonlinear heart rate control in a healthy population,” American J. of Physiology Heart and Circulatory Physiology, Vol.290, H2560-H2570, 2006.
  23. [23] P. Allegrini et al., “Spontaneous brain activity as a source of ideal 1/f noise,” Physical Review E: Statical Nonlinear and Soft Matter Physics, Vol.80, 061914, 2009.
  24. [24] W. J. Freeman and J. Zhia, “Simulated power spectral density (PSD) of background electrocorticogram (ECoG),” Cognitive Neurodynamics, Vol.3, No.1, pp. 97-103, 2009.
  25. [25] B. J. Westest, E. L. Geneston, and P. Grigolini, “Maximizing information exchange between complex network,” Physics. Report, Vol.468, pp. 1-99, 2008.
  26. [26] D. L. Gilden, T. Thoronton, andM.W.Mallon, “1/f Noise in Human Cognition,” Science, Vol.24, No.5205, pp. 1837-1839, 1995.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Jun. 03, 2024