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Fuzzy control in robot-soccer, evolutionary learning in the first layer of control

conference contribution
posted on 06.12.2017, 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.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Start Page

181

End Page

186

Number of Pages

6

Start Date

14/07/2002

Finish Date

18/07/2002

ISBN-10

9800781501

ISBN-13

9789800781500

Location

Orlando, Florida.

Publisher

International Institute of Informatics and Systemics

Place of Publication

Florida, USA

Peer Reviewed

Yes

Open Access

No

Cultural Warning

This 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 Affiliations

Faculty of Engineering and Physical Systems; Faculty of Informatics and Communication;

Era Eligible

No

Name of Conference

6th World Multiconference on Systemics, Cybernetics and Informatics

Parent Title

Proceedings of The 6th World Multiconference on Systemics, Cybernetics and Informatics