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Fuzzy control in robot-soccer, evolutionary learning in the first layer of control
conference contributionposted on 2017-12-06, 00:00 authored by Peter ThomasPeter Thomas, Russel StonierRussel Stonier
In this paper an evolutionary algorithm is developed to learn a fuzzy knowledge base for the control of a soccer playing micro-robot from any configuration belonging to a grid of initial configurations to hit the ball along the ball to goal line of sight. The knowledge base uses relative co-ordinate system including left and right wheel velocities of the robot. Final path positions allow forward and reverse facing robot to ball and include its physical dimensions.
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)
Number of Pages6
PublisherInternational Institute of Informatics and Systemics
Place of PublicationFlorida, USA
Cultural WarningThis research output may contain the names and images of Aboriginal and Torres Strait Islander people now deceased. We apologize for any distress that may occur.
External Author AffiliationsFaculty of Engineering and Physical Systems; Faculty of Informatics and Communication;