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Improvement of Kinect(TM) Sensor Capabilities by Fusion with Laser Sensing Data Using Octree

To enhance sensor capabilities, sensor data readings from different modalities must be fused. The main contribution of this paper is to present a sensor data fusion approach that can reduce Kinect(TM) sensor limitations. This approach involves combining laser with Kinect(TM) sensors. Sensor data is...

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Detalles Bibliográficos
Autores principales: Chávez, Alfredo, Karstoft, Henrik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3355387/
https://www.ncbi.nlm.nih.gov/pubmed/22666006
http://dx.doi.org/10.3390/s120403868
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author Chávez, Alfredo
Karstoft, Henrik
author_facet Chávez, Alfredo
Karstoft, Henrik
author_sort Chávez, Alfredo
collection PubMed
description To enhance sensor capabilities, sensor data readings from different modalities must be fused. The main contribution of this paper is to present a sensor data fusion approach that can reduce Kinect(TM) sensor limitations. This approach involves combining laser with Kinect(TM) sensors. Sensor data is modelled in a 3D environment based on octrees using a probabilistic occupancy estimation. The Bayesian method, which takes into account the uncertainty inherent in the sensor measurements, is used to fuse the sensor information and update the 3D octree map. The sensor fusion yields a significant increase of the field of view of the Kinect(TM) sensor that can be used for robot tasks.
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spelling pubmed-33553872012-06-04 Improvement of Kinect(TM) Sensor Capabilities by Fusion with Laser Sensing Data Using Octree Chávez, Alfredo Karstoft, Henrik Sensors (Basel) Article To enhance sensor capabilities, sensor data readings from different modalities must be fused. The main contribution of this paper is to present a sensor data fusion approach that can reduce Kinect(TM) sensor limitations. This approach involves combining laser with Kinect(TM) sensors. Sensor data is modelled in a 3D environment based on octrees using a probabilistic occupancy estimation. The Bayesian method, which takes into account the uncertainty inherent in the sensor measurements, is used to fuse the sensor information and update the 3D octree map. The sensor fusion yields a significant increase of the field of view of the Kinect(TM) sensor that can be used for robot tasks. Molecular Diversity Preservation International (MDPI) 2012-03-26 /pmc/articles/PMC3355387/ /pubmed/22666006 http://dx.doi.org/10.3390/s120403868 Text en © 2012 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Chávez, Alfredo
Karstoft, Henrik
Improvement of Kinect(TM) Sensor Capabilities by Fusion with Laser Sensing Data Using Octree
title Improvement of Kinect(TM) Sensor Capabilities by Fusion with Laser Sensing Data Using Octree
title_full Improvement of Kinect(TM) Sensor Capabilities by Fusion with Laser Sensing Data Using Octree
title_fullStr Improvement of Kinect(TM) Sensor Capabilities by Fusion with Laser Sensing Data Using Octree
title_full_unstemmed Improvement of Kinect(TM) Sensor Capabilities by Fusion with Laser Sensing Data Using Octree
title_short Improvement of Kinect(TM) Sensor Capabilities by Fusion with Laser Sensing Data Using Octree
title_sort improvement of kinect(tm) sensor capabilities by fusion with laser sensing data using octree
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3355387/
https://www.ncbi.nlm.nih.gov/pubmed/22666006
http://dx.doi.org/10.3390/s120403868
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