Context-Awareness at the Service of Sensor Fusion Systems: Inverting the Usual Scheme
Editorial:
Springer
Fecha de edición:
2011
Cita:
Cabestani, J. et al. (eds.) (2011). Advances in Computational Intelligence: 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, Torremolinos-Málaga, Spain, June 8-10, 2011, Proceedings, Part II. (Lecture Notes in Computer Science, 6692). Springer, 653-660.
ISBN:
978-3-642-21498-1 (online)
978-3-642-21497-4 (print)
ISSN:
0302-9743 (print)
1611-3349 (online)
DOI:
10.1007/978-3-642-21498-1_82
Patrocinador:
This work was supported in part by Projects ATLANTIDA, CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, SINPROB, CAM MADRINET S-0505/TIC/0255 DPS2008-07029-C02-02.
Serie/Num.:
Lecture Notes in Computer Science
6692
Palabras clave:
Sensor fusion
,
Navigation
,
Indoor
,
Outdoor
,
Context-Aware
,
Particle filter
,
Software agent
Derechos:
© 2011 Springer-Verlag Berlin Heidelberg
Resumen:
Many works on context-aware systems make use of location, navigation or tracking services offered by an underlying sensor fusion module, as part of the relevant contextual information. The obtained knowledge is typically consumed only by the high level layers
Many works on context-aware systems make use of location, navigation or tracking services offered by an underlying sensor fusion module, as part of the relevant contextual information. The obtained knowledge is typically consumed only by the high level layers of the system, in spite that context itself represents a valuable source of information from which every part of the implemented system could take benefit. This paper closes the loop, analyzing how can context knowledge be applied to improve the accuracy, robustness and adaptability of sensor fusion processes. The whole theoretical analysis will be related with the indoor/outdoor navigation system implemented for a wheeled robotic platform. Some preliminary results are presented, where the context information provided by a map is integrated in the sensor fusion system.
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Nota:
Proceedings of: 11th International Work-Conference on Artificial Neural Networks (IWANN 2011). International Workshop of Intelligent systems for context-based information fusion (ISCIF 11). Torremolinos-Málaga, Spain, June 8-10, 2011
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