Online Learning and Adaptation of Autonomous Mobile Robots for Sustainable Agriculture

Authors:
Hani Hagras;Martin Colley;Victor Callaghan;Malcolm Carr-West
Affiliations:
Department of Computer Science, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, England, UK;Department of Computer Science, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, England, UK;Department of Computer Science, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, England, UK;The Agricultural Engineering Department, University College Writtle, England, UK
Venue:
Autonomous Robots
Year:
2002

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Abstract

In this paper we will introduce the application of our newly patented double hierarchical Fuzzy-Genetic system (British patent 99-10539.7) to produce an intelligent autonomous outdoor agricultural mobile robot capable of learning and calibrating its controller online in a short time interval and implementing a life long learning strategy. The online and life long learning strategy allow the outdoor robots to increase their experience and adapt their controllers in the face of the changing and dynamic unstructured outdoor agricultural environments. Such characteristics permit prolonged periods of operation within dynamic agricultural environments, which is an essential feature for the realization of a platform vehicle for use in sustainable agriculture and organic farming.