Appearance-based robotics - Robot localization in partially explored environments

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