A hybrid intelligent system for robot ego motion estimation with a 3D camera

Ivan Villaverde; Manuel Graña

doi:10.1007/978-3-540-87656-4_81

A hybrid intelligent system for robot ego motion estimation with a 3D camera

Ivan Villaverde^*
, Manuel Graña

^*Autor correspondiente de este trabajo

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

4 Citas (Scopus)

Resumen

A Hybrid Intelligent System (HIS) for self-localization working on the readings of innovative 3D cameras is presented in this paper. The system includes a preprocessing step for cleaning the 3D camera readings. The HIS consist of two main modules. First the Self-Organizing Map (SOM) is used to provide models of the preprocessed 3D readings of the camera. The 2D grid of the SOM units is assumed as a surface modeling the 3D data obtained from each snapshot of the 3D camera. The second module is an Evolution Strategy, which is used to perform the estimation of the motion of the robot between frames. The fitness function of the Evolution Strategy (ES) is given by the distance computed as the matching of the SOM unit grids.

Idioma original	Inglés
Título de la publicación alojada	Hybrid Artificial Intelligence Systems - Third International Workshop, HAIS 2008, Proceedings
Páginas	657-664
Número de páginas	8
DOI	https://doi.org/10.1007/978-3-540-87656-4_81
Estado	Publicada - 2008
Publicado de forma externa	Sí
Evento	3rd International Workshop on Hybrid Artificial Intelligence Systems, HAIS 2008 - Burgos, Espana Duración: 24 sept 2008 → 26 sept 2008

Serie de la publicación

Nombre	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen	5271 LNAI
ISSN (versión impresa)	0302-9743
ISSN (versión digital)	1611-3349

Conferencia

Conferencia	3rd International Workshop on Hybrid Artificial Intelligence Systems, HAIS 2008
País/Territorio	Espana
Ciudad	Burgos
Período	24/09/08 → 26/09/08

Acceder al documento

10.1007/978-3-540-87656-4_81

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Villaverde, I., & Graña, M. (2008). A hybrid intelligent system for robot ego motion estimation with a 3D camera. En Hybrid Artificial Intelligence Systems - Third International Workshop, HAIS 2008, Proceedings (pp. 657-664). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5271 LNAI). https://doi.org/10.1007/978-3-540-87656-4_81

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title = "A hybrid intelligent system for robot ego motion estimation with a 3D camera",

abstract = "A Hybrid Intelligent System (HIS) for self-localization working on the readings of innovative 3D cameras is presented in this paper. The system includes a preprocessing step for cleaning the 3D camera readings. The HIS consist of two main modules. First the Self-Organizing Map (SOM) is used to provide models of the preprocessed 3D readings of the camera. The 2D grid of the SOM units is assumed as a surface modeling the 3D data obtained from each snapshot of the 3D camera. The second module is an Evolution Strategy, which is used to perform the estimation of the motion of the robot between frames. The fitness function of the Evolution Strategy (ES) is given by the distance computed as the matching of the SOM unit grids.",

keywords = "Evolutive computation, Robot navigation, Self organizing maps",

author = "Ivan Villaverde and Manuel Gra{\~n}a",

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doi = "10.1007/978-3-540-87656-4\_81",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "657--664",

booktitle = "Hybrid Artificial Intelligence Systems - Third International Workshop, HAIS 2008, Proceedings",

note = "3rd International Workshop on Hybrid Artificial Intelligence Systems, HAIS 2008 ; Conference date: 24-09-2008 Through 26-09-2008",

}

Villaverde, I & Graña, M 2008, A hybrid intelligent system for robot ego motion estimation with a 3D camera. En Hybrid Artificial Intelligence Systems - Third International Workshop, HAIS 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5271 LNAI, pp. 657-664, 3rd International Workshop on Hybrid Artificial Intelligence Systems, HAIS 2008, Burgos, Espana, 24/09/08. https://doi.org/10.1007/978-3-540-87656-4_81

A hybrid intelligent system for robot ego motion estimation with a 3D camera. / Villaverde, Ivan; Graña, Manuel.
Hybrid Artificial Intelligence Systems - Third International Workshop, HAIS 2008, Proceedings. 2008. p. 657-664 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5271 LNAI).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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AB - A Hybrid Intelligent System (HIS) for self-localization working on the readings of innovative 3D cameras is presented in this paper. The system includes a preprocessing step for cleaning the 3D camera readings. The HIS consist of two main modules. First the Self-Organizing Map (SOM) is used to provide models of the preprocessed 3D readings of the camera. The 2D grid of the SOM units is assumed as a surface modeling the 3D data obtained from each snapshot of the 3D camera. The second module is an Evolution Strategy, which is used to perform the estimation of the motion of the robot between frames. The fitness function of the Evolution Strategy (ES) is given by the distance computed as the matching of the SOM unit grids.

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KW - Self organizing maps

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Villaverde I, Graña M. A hybrid intelligent system for robot ego motion estimation with a 3D camera. En Hybrid Artificial Intelligence Systems - Third International Workshop, HAIS 2008, Proceedings. 2008. p. 657-664. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-87656-4_81

A hybrid intelligent system for robot ego motion estimation with a 3D camera

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