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Dense Map Inference with User-Defined Priors: From Priorlets to Scan Eigenvariations
Cita
Puente Yusty, Paloma de la 
ORCID: https://orcid.org/0000-0002-8652-0300 and Censi, Andrea
(2012).
Dense Map Inference with User-Defined Priors: From Priorlets to Scan Eigenvariations.
En: "Spatial Cognition VIII", 01/09/2012 - 03/09/2012, Kloster Seeon, Bavaria, Alemania. ISBN 978-3-642-32732-2_6. pp. 94-113.
ORCID: https://orcid.org/0000-0002-8652-0300 and Censi, Andrea
(2012).
Dense Map Inference with User-Defined Priors: From Priorlets to Scan Eigenvariations.
En: "Spatial Cognition VIII", 01/09/2012 - 03/09/2012, Kloster Seeon, Bavaria, Alemania. ISBN 978-3-642-32732-2_6. pp. 94-113.
Descripción
| Título: | Dense Map Inference with User-Defined Priors: From Priorlets to Scan Eigenvariations |
|---|---|
| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | Spatial Cognition VIII |
| Fechas del Evento: | 01/09/2012 - 03/09/2012 |
| Lugar del Evento: | Kloster Seeon, Bavaria, Alemania |
| Título del Libro: | Spatial Cognition VIII. Lecture Notes in Computer Science |
| Fecha: | 2012 |
| ISBN: | 978-3-642-32732-2_6 |
| Volumen: | 7463 |
| Materias: | |
| ODS: | |
| Escuela: | E.T.S.I. Industriales (UPM) |
| Departamento: | Automática, Ingeniería Electrónica e Informática Industrial [hasta 2014] |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
Resumen
When mapping is formulated in a Bayesian framework, the need of specifying a prior for the environment arises naturally. However, so far, the use of a particular structure prior has been coupled to working with a particular representation. We describe a system that supports inference with multiple priors while keeping the same dense representation. The priors are rigorously described by the user in a domain-specific language. Even though we work very close to the measurement space, we are able to represent structure constraints with the same expressivity as methods based on geometric primitives. This approach allows the intrinsic degrees of freedom of the environment’s shape to be recovered. Experiments with simulated and real data sets will be presented
Más información
| ID de Registro: | 13703 |
|---|---|
| Identificador DC: | https://oa.upm.es/13703/ |
| Identificador OAI: | oai:oa.upm.es:13703 |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 20 Nov 2012 10:37 |
| Ultima Modificación: | 21 Abr 2016 13:02 |
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