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VGI_SLAM

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Deriving Spatial Data from Volunteered Geographic Information

Recent years have seen the widespread engagement of large numbers of private citizens in the creation of spatial data. These contributors, commonly referred to as citizen sensors, often have no formal qualifications in performing... ver más

31/08/2015

NUID UCD

178K€

Presupuesto del proyecto: 178K€

Líder del proyecto

UNIVERSITY COLLEGE DUBLIN NATIONAL UNIVERSITY... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2015-08-31 No tenemos la información de la convocatoria

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1 Participantes

NUID UCD

0.00€ | Lider

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Líder del proyecto

UNIVERSITY COLLEGE DUBLIN NATIONAL UNIVERSITY... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 178K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Recent years have seen the widespread engagement of large numbers of private citizens in the creation of spatial data. These contributors, commonly referred to as citizen sensors, often have no formal qualifications in performing a task which was traditionally reserved to official mapping agencies. This paradigm of crowd sourced spatial data is commonly referred to as Volunteered Geographic Information (VGI) (Goodchild, 2007). The greatest concern when using any form of spatial data is its quality. Therefore the data derived from VGI should be of the highest possible quality and it is necessary to be able to make statements about this quality. These tasks are complicated by the fact that VGI may be captured with inaccurate devices, lacking detail and in some cases inconsistent. Consequently there exists a degree of uncertainty associated with VGI which must be considered if one is to derive accurate spatial data. The overall objective of the proposed research project is the development of new methodologies for deriving spatial data from VGI using a probabilistic formulation. We proposed to draw heavily from methodologies developed in the domain of robotics and specifically the sub-domain of Simultaneous Localization And Mapping (SLAM). Dr. Corcoran has much previous research experience in VGI and SLAM, and therefore is a suitable candidate to carry out the project in question. Prof. Leonard of Massachusetts Institute of Technology (MIT) and Dr. Bertolotto of University College Dublin (UCD) are experts in the areas of robotics and geographical information science respectively. Their institutes therefore represent suitable hosts for Dr. Corcoran. The result of this fellowship will be a significant and long lasting transfer of knowledge and skills from MIT to UCD.

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