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Lee, Chee Sing
Nagappa, Sharad Palomeras Rovira, NarcÃs Clark, Daniel E. Salvi, Joaquim |
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2014 | |
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 | |
application/pdf | |
1070-9932 | |
http://hdl.handle.net/10256/10211 | |
eng | |
Institute of Electrical and Electronics Engineers (IEEE) | |
Reproducció digital del document publicat a: http://dx.doi.org/10.1109/MRA.2014.2310132 Articles publicats (D-ATC) info:eu-repo/grantAgreement/EC/FP7/288273 |
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© IEEE Robotics and Automation Magazine, 2014, vol. 21, p. 38-45 | |
Tots els drets reservats | |
Vehicles submergibles
Submersibles Algorismes computacionals Computer algorithms Robots mòbils Mobile robots |
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SLAM with SC-PHD filters: an underwater vehicle application | |
info:eu-repo/semantics/article | |
DUGiDocs |