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Generating Cooperative Collective Behavior in Swarm Robotic Systems

Kazuhiro Ohkura, Toshiyuki Yasuda, Yoshiyuki Matsumura

Year
2013
Citations
3

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.

Keywords

Swarm roboticsComputer scienceEvolutionary roboticsArtificial intelligenceArtificial neural networkRoboticsSwarm behaviourFlexibility (engineering)RobotPhysical neural network

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