Robot localization has been recognized as one of the most fundamental problems in mobile robotics. Localization can be defined as the problem of determining the position of a robot. More precisely, the aim of localization is to estimate the position of a robot in its environment, given local sensorial data. This information is essential for a broad range of mobile robots tasks; in particular, the robot behavior may depend on its position. This article presents a novel and efficient metric for appearance based robot localization. This metric is integrated in a framework that uses a partially observable Markov decision process as position evaluator, thus allowing good results even in partially explored environments and in highly perceptually aliased indoor scenarios.

Appearance-based robotics - Robot localization in partially explored environments

ZINGARETTI, PRIMO;FRONTONI, EMANUELE
2006

Abstract

Robot localization has been recognized as one of the most fundamental problems in mobile robotics. Localization can be defined as the problem of determining the position of a robot. More precisely, the aim of localization is to estimate the position of a robot in its environment, given local sensorial data. This information is essential for a broad range of mobile robots tasks; in particular, the robot behavior may depend on its position. This article presents a novel and efficient metric for appearance based robot localization. This metric is integrated in a framework that uses a partially observable Markov decision process as position evaluator, thus allowing good results even in partially explored environments and in highly perceptually aliased indoor scenarios.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/37592
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