Observation of Synchronization Phenomena in Structured Flocking Behavior

Sho Yamauchi; Hidenori Kawamura; Keiji Suzuki

doi:10.20965/jaciii.2013.p0715

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JACIII Vol.17 No.5 pp. 715-720

doi: 10.20965/jaciii.2013.p0715

(2013)

Paper:

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Observation of Synchronization Phenomena in Structured Flocking Behavior

Sho Yamauchi, Hidenori Kawamura, and Keiji Suzuki

Graduate School of Information Science and Technology, Hokkaido University, North 14 West 9, Sapporo, Hokkaido, Japan

Received:

March 20, 2013

Accepted:

June 19, 2013

Published:

September 20, 2013

Keywords:

flocking algorithm, autonomous system, synchronization

Abstract

Flocking algorithms for multi-agent systems are distributed algorithms that generate complex formational movement despite having simple rules for each agent. These algorithms, known as swarmintelligence, are flexible and robust. However, to exploit these features to generate flexible behavior in an autonomous system, greater flexibility is needed. To achieve this, these algorithms are extended to enable arbitrary lattice formation. In addition, extended flocking algorithms can be assumed to be the aggregation of oscillators and observed the behavior of synchronization. It is difficult to explain the behavior of extended flocking algorithms as a consensus problem but, by assuming the flock as the set of oscillators, it can be explained as a synchronization phenomenon.

Cite this article as:

S. Yamauchi, H. Kawamura, and K. Suzuki, “Observation of Synchronization Phenomena in Structured Flocking Behavior,” J. Adv. Comput. Intell. Intell. Inform., Vol.17, No.5, pp. 715-720, 2013.

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References

[1] C. Reynolds, “Flocks, herds and schools: A distributed behavioral model,” ACMSIGGRAPH Computer Graphics, ACM, Vol.21, No.4, pp. 25-34, 1987.
[2] E. Bonabeau, M. Dorigo, and G. Théraulaz, “From natural to artificial swarm intelligence,” 1999.
[3] E. Bonabeau, M. Dorigo, and G. Theraulaz, “Inspiration for optimization from social insect behaviour,” Nature, Vol.406, No.6791, pp. 39-42, 2000.
[4] A.Williams, S. Glavaski, and T. Samad, “Formations of formations: Hierarchy and stability,” American Control Conf., 2004, Proc. of the 2004, IEEE, Vol.4, pp. 2992-2997, 2004.
[5] R. Olfati-Saber, “Flocking for multi-agent dynamic systems: Algorithms and theory,” IEEE Trans. on, Automatic Control, Vol.51, No.3, pp. 401-420, 2006.
[6] B. Jakimovski, B. Meyer, and E. Maehle, “Self-reconfiguring hexapod robot OSCAR using organically inspired approaches and innovative robot leg amputation mechanism,” Int. Conf. on Automation, Robotics and Control Systems, ARCS-09, Orlando, USA, 2009.
[7] S. Yamauchi, H. Kawamura, and K. Suzuki, “Extended flocking algorithm for self-parameter tuning,” IEEJ Trans. on Electronics, Information and Systems, Vol.133, Sec.C, No.6, pp. 1195-1201, 2013.
[8] S. Nakata, T. Miyata, N. Ojima, and K. Yoshikawa, “Selfsynchronization in coupled salt-water oscillators,” Physica D: Nonlinear Phenomena, Vol.115, No.3, pp. 313-320, 1998.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] C. Reynolds, “Flocks, herds and schools: A distributed behavioral model,” ACMSIGGRAPH Computer Graphics, ACM, Vol.21, No.4, pp. 25-34, 1987.

[2] [2] E. Bonabeau, M. Dorigo, and G. Théraulaz, “From natural to artificial swarm intelligence,” 1999.

[3] [3] E. Bonabeau, M. Dorigo, and G. Theraulaz, “Inspiration for optimization from social insect behaviour,” Nature, Vol.406, No.6791, pp. 39-42, 2000.

[4] [4] A.Williams, S. Glavaski, and T. Samad, “Formations of formations: Hierarchy and stability,” American Control Conf., 2004, Proc. of the 2004, IEEE, Vol.4, pp. 2992-2997, 2004.

[5] [5] R. Olfati-Saber, “Flocking for multi-agent dynamic systems: Algorithms and theory,” IEEE Trans. on, Automatic Control, Vol.51, No.3, pp. 401-420, 2006.

[6] [6] B. Jakimovski, B. Meyer, and E. Maehle, “Self-reconfiguring hexapod robot OSCAR using organically inspired approaches and innovative robot leg amputation mechanism,” Int. Conf. on Automation, Robotics and Control Systems, ARCS-09, Orlando, USA, 2009.

[7] [7] S. Yamauchi, H. Kawamura, and K. Suzuki, “Extended flocking algorithm for self-parameter tuning,” IEEJ Trans. on Electronics, Information and Systems, Vol.133, Sec.C, No.6, pp. 1195-1201, 2013.

[8] [8] S. Nakata, T. Miyata, N. Ojima, and K. Yoshikawa, “Selfsynchronization in coupled salt-water oscillators,” Physica D: Nonlinear Phenomena, Vol.115, No.3, pp. 313-320, 1998.