Biology inspired robot behavior selection mechanism: using genetic algorithm

Authors:
Yiping Wang;Sheng Li;Qingwei Chen;Weili Hu
Affiliations:
Automation School, Nanjing University of Science & Technology, Nanjing, China;Automation School, Nanjing University of Science & Technology, Nanjing, China;Automation School, Nanjing University of Science & Technology, Nanjing, China;Automation School, Nanjing University of Science & Technology, Nanjing, China
Venue:
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
Year:
2007

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Abstract

Since behavior selection is a crucial issue not only in biology, but also in robotics, especially in behavior-based robotics, it is nature to consider the behavior selection problem both in biological view and robotic view. In recent years, accumulative evidences from neurobiology and anatomy have given rise to proposals that the basal ganglia-a group of subcortex nuclei in vertebrate brains- serve as a central selection mechanism. This paper introduces a robot behavior selection mechanism inspired by basal ganglia and makes explorations of applying genetic algorithm to the optimization of model parameters. The proposed method demonstrates its efficiency through a simulated robot foraging task and casts light on designing more intelligent and fluent behavior selection mechanism in the future.