Generating Cooperative Collective Behavior in Swarm Robotic Systems | Zendy

Kazuhiro Ohkura | Zendy; Toshiyuki Yasuda | Zendy; Yoshiyuki Matsumura | Zendy

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Generating Cooperative Collective Behavior in Swarm Robotic Systems

Author(s) -

Kazuhiro Ohkura,

Toshiyuki Yasuda,

Yoshiyuki Matsumura

Publication year - 2013

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2013.p0699

Subject(s) - swarm robotics , computer science , evolutionary robotics , artificial intelligence , artificial neural network , robotics , swarm behaviour , flexibility (engineering) , robot , physical neural network , network topology , swarm intelligence , topology (electrical circuits) , nervous system network models , artificial life , time delay neural network , types of artificial neural networks , machine learning , particle swarm optimization , mathematics , statistics , combinatorics , operating system

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.

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