LIVCODE

Life-like visual information processing for robust collision detection

Coordinatore	UNIVERSITY OF LINCOLN    more  Organization address address: Brayford Pool city: LINCOLN postcode: LN6 7TS contact info Titolo: Dr. Nome: Shigang Cognome: Yue Email: send email Telefono: +44 1522 837397 Fax: +44 1512 886974
Nazionalità Coordinatore	United Kingdom [UK]
Totale costo	728˙500 €
EC contributo	724˙500 €
Programma	FP7-PEOPLE Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	FP7-PEOPLE-2011-IRSES
Funding Scheme	MC-IRSES
Anno di inizio	2012
Periodo (anno-mese-giorno)	2012-10-01   -   2016-09-30

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	UNIVERSITY OF LINCOLN  Organization address address: Brayford Pool city: LINCOLN postcode: LN6 7TS contact info Titolo: Dr. Nome: Shigang Cognome: Yue Email: send email Telefono: +44 1522 837397 Fax: +44 1512 886974	UK (LINCOLN)	coordinator	472˙500.00
2	UNIVERSITAET HAMBURG  Organization address address: EDMUND-SIEMERS-ALLEE 1 city: HAMBURG postcode: 20146 contact info Titolo: Mr. Nome: Tim Cognome: Scharfenberg Email: send email Telefono: +49 40 42883 2203 Fax: +49 40 42883 2206	DE (HAMBURG)	participant	168˙000.00
3	UNIVERSITY OF NEWCASTLE UPON TYNE  Organization address address: Kensington Terrace 6 city: NEWCASTLE UPON TYNE postcode: NE1 7RU contact info Titolo: Dr. Nome: Amanda Cognome: Gregory Email: send email Telefono: +44 191 2824514	UK (NEWCASTLE UPON TYNE)	participant	84˙000.00

Mappa

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 Obiettivo del progetto (Objective)

'To be able to detected collision efficiently is of vital importance for the survival of animals that are migrating at speed, especially for those flying in dense swarms like locusts. Vision plays a critical role in collision detection for most animal species in a dynamic world. It is expected that in future, many human made machines, such like ground vehicles, mobile robots, and unmanned aerial vehicles, should all be able to detect and avoid collisions effectively as animals do. The challenge to achieve this is huge. Biological visual neural systems provide ideal models to achieve this goal.

LIVCODE consortium focuses on robust solutions for visual based collision detection. Taking the inspiration from biological visual systems, the consortium will bring neurobiologists, neural system modellers, chip designers, and robotic researchers together and complement each others’ research strengths via staff secondments, and jointly organised seminars and workshops. The consortium will investigate robust solutions for collision detection in the real world, through neural system modelling, neural model integration, chip realization and application, in order to build strong connections between the European institutions and partner institutions in a fast growing economy.

Six work packages (WPs) are designed to achieve the objectives of the project:

WP0: Project management, WP1: Biological plausible visual neural system modelling, WP2: Multiple visual neural systems integration, WP3: VLSI neural vision chip design, WP4: Neural vision systems for mobile robots and unmanned aerial systems, and WP5: Dissemination, exploitation, business model.'