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Set membership localization of mobile robots via angle measurements

Andrea Garulli, Antonio Vicino

Year
2001
Citations
65

Abstract

This paper addresses the localization problem for a mobile robot navigating in an unstructured outdoor environment. A new technique is introduced, for computing an estimate of the position of the robot and the related uncertainty region, in the presence of visual angle measurements affected by bounded errors. The proposed set membership estimation procedure exploits the structure of the static set estimator, to solve recursively the dynamic localization problem.

Keywords

Mobile robotEstimatorRobotSet (abstract data type)Computer sciencePosition (finance)Bounded functionExploitMonte Carlo localizationComputer vision

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