Kernel Characterization of an Interval Function

This paper proposes a set-membership approach to characterize the kernel of an interval-valued function. In the context of a bounded-error estimation, this formulation makes it possible to embed all uncertainties of the problem inside the interval function and thus to avoid bisections with respect t...

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Bibliographic Details
Published in:	Mathematics in computer science Vol. 8; no. 3-4; pp. 379 - 390
Main Authors:	Aubry, Clément, Desmare, Rozenn, Jaulin, Luc
Format:	Journal Article
Language:	English
Published:	Basel Springer Basel 01-09-2014 Springer
Subjects:	Automatic Computer Science Engineering Sciences Mathematics Mathematics and Statistics Interval analysis Loop closure 65G20 65G4 65G30 Localization Kernel Robotics localization robotics interval analysis kernel loop closure
Online Access:	Get full text
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Summary:	This paper proposes a set-membership approach to characterize the kernel of an interval-valued function. In the context of a bounded-error estimation, this formulation makes it possible to embed all uncertainties of the problem inside the interval function and thus to avoid bisections with respect to all these uncertainties. To illustrate the principle of the approach, two testcases taken from robotics will be presented. The first testcase deals with the characterization of all loops of a mobile robot from proprioceptive measurements only. The second testcase is the localization of a robot from range-only measurements.
ISSN:	1661-8270 1661-8289
DOI:	10.1007/s11786-014-0206-9