GARNICS

Gardening with a Cognitive System

Coordinatore	FORSCHUNGSZENTRUM JUELICH GMBH    more  Organization address address: WILHELM-JOHNEN-STRASSE city: JUELICH postcode: 52428 contact info Nome: Petra Cognome: Insberg Email: send email Telefono: -614739 Fax: -614530
Nazionalità Coordinatore	Germany [DE]
Totale costo	3˙721˙066 €
EC contributo	2˙871˙000 €
Programma	FP7-ICT Specific Programme "Cooperation": Information and communication technologies
Code Call	FP7-ICT-2009-4
Funding Scheme	CP
Anno di inizio	2010
Periodo (anno-mese-giorno)	2010-03-01   -   2013-02-28

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	FORSCHUNGSZENTRUM JUELICH GMBH  Organization address address: WILHELM-JOHNEN-STRASSE city: JUELICH postcode: 52428 contact info Nome: Petra Cognome: Insberg Email: send email Telefono: -614739 Fax: -614530	DE (JUELICH)	coordinator	0.00
2	AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS  Organization address address: CALLE SERRANO city: MADRID postcode: 28006 contact info Titolo: Mr. Nome: Carlos Manuel Cognome: Abad Ruiz Email: send email Telefono: +34 91 566 8852 Fax: +34 91 566 89 13	ES (MADRID)	participant	0.00
3	GEORG-AUGUST-UNIVERSITAET GOETTINGEN STIFTUNG OEFFENTLICHEN RECHTS  Organization address address: WILHELMSPLATZ city: GOETTINGEN postcode: 37073 contact info Titolo: Ms. Nome: Ursula Cognome: Hahn-Woergoetter Email: send email Telefono: +49 (0)551 3910769 Fax: +49 (0)551 397720	DE (GOETTINGEN)	participant	0.00
4	LINKOPINGS UNIVERSITET  Organization address address: CAMPUS VALLA city: LINKOPING postcode: 581 83 contact info Titolo: Ms. Nome: Christina Cognome: Henriksson Email: send email Telefono: +46 13 281084 Fax: 46138526	SE (LINKOPING)	participant	0.00

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 Obiettivo del progetto (Objective)

The GARNICS project aims at 3D sensing of plant growth and building perceptual representations for learning the links to actions of a robot gardener. Plants are complex, self-changing systems with increasing complexity over time. Actions performed at plants (like watering), will have strongly delayed effects. Thus, monitoring and controlling plants is a difficult perception-action problem requiring advanced predictive cognitive properties, which so far can only be provided by experienced human gardeners. Sensing and control of a plants actual properties, i.e. its phenotype, is relevant to e.g. seed production and plant breeders. We address plant sensing and control by combining active vision with appropriate perceptual representations, which are essential for cognitive interactions. Core ingredients for these representations are channel representations, dynamic graphs and cause-effect couples (CECs). Channel representations are a wavelet-like, biologically motivated information representation, which can be generalized coherently using group theory. Using these representations, plant models -- represented by dynamic graphs -- will be acquired and by interacting with a human gardener the system will be taught the different cause-effect relations resulting from possible treatments. Employing decision making and planning processes via CECs, our robot gardener will then be able to choose from its learned repertoire the appropriate actions for optimal plant growth. This way we will arrive at an adaptive, interactive cognitive system, which will be implemented and tested in an industrially-relevant plant-phenotyping application.