DUGiDocsSLAM with SC-PHD filters: an underwater vehicle application
dc.contributor.author
dc.date.accessioned
2015-03-25T12:22:59Z
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2015-03-25T12:22:59Z
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2014
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1070-9932
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dc.description.abstract
The random finite-set formulation for multiobject estimation provides a means of estimating the number of objects in cluttered environments with missed detections within a unified probabilistic framework. This methodology is now becoming the dominant mathematical framework within the sensor fusion community for developing multiple-target tracking algorithms. These techniques are also gaining traction in the field of feature-based simultaneous localization and mapping (SLAM) for mobile robotics. Here, we present one such instance of this approach with an underwater vehicle using a hierarchical multiobject estimation method for estimating both landmarks and vehicle position
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application/pdf
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eng
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Institute of Electrical and Electronics Engineers (IEEE)
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Reproducció digital del document publicat a: http://dx.doi.org/10.1109/MRA.2014.2310132
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© IEEE Robotics and Automation Magazine, 2014, vol. 21, p. 38-45
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Articles publicats (D-ATC)
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Tots els drets reservats
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dc.title
SLAM with SC-PHD filters: an underwater vehicle application
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info:eu-repo/semantics/article
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info:eu-repo/semantics/embargoedAccess
dc.embargo.terms
Cap
dc.date.embargoEndDate
info:eu-repo/date/embargoEnd/2026-01-01
dc.relation.projectID
info:eu-repo/grantAgreement/EC/FP7/288273/EU/Persistent Autonomy through Learning, Adaptation, Observation and Re-planning/PANDORA
dc.type.version
info:eu-repo/semantics/publishedVersion
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