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JACIII Vol.17 No.5 pp. 699-706
doi: 10.20965/jaciii.2013.p0699
(2013)

Paper:

Generating Cooperative Collective Behavior in Swarm Robotic Systems

Kazuhiro Ohkura*, Toshiyuki Yasuda*, and Yoshiyuki Matsumura**

*Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima 739-8527, Japan

**Faculty of Textile Science and Technology, Shinshu University, 3-15-1 Tokida, Ueda, Nagano 386-8567, Japan

Received:
April 13, 2013
Accepted:
May 21, 2013
Published:
September 20, 2013
Keywords:
swarm robotics, evolutionary robotics, topology and weight evolving artificial neural network (TWEANN), MBEANN
Abstract

Swarm robotics research involves multirobot systems that consist of many homogeneous autonomous robots but no global controller. In this paper, an evolutionary robotics approach using an artificial neural network is applied to a swarm robotic system. Conventionally, the neural network evolved using only synaptic weights under the condition of a fixed topology. Our research group has been developing a novel approach to a topology and weight evolving artificial neural network named Mutation-Based Evolving Artificial Neural Network (MBEANN). A series of computer simulations shows that MBEANN yields better results in terms of flexibility than conventional solutions to the cooperative package-pushing problem.

Cite this article as:
Kazuhiro Ohkura, Toshiyuki Yasuda, and Yoshiyuki Matsumura, “Generating Cooperative Collective Behavior in Swarm Robotic Systems,” J. Adv. Comput. Intell. Intell. Inform., Vol.17, No.5, pp. 699-706, 2013.
Data files:
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