1,721,365 research outputs found
Vision based mobile robotics. Mobile robot localization using vision sensors and active probabilistic approaches
No full textThe use of vision in mobile robotics in one of the main goal of this thesis. In particular novel appearance based approaches for image matching metric are introduced. These approaches are applied to the problem of mobile robot localization. Similarity measures between robot’s views are used in probabilistic methods for robot pose estimation. In this field of probabilistic localization active approach are proposed allowing the robot to faster and better localize. All methods have been extensively tested using a real robot in an indoor environment
Vision based mobile robotics. Mobile robot localization using vision sensors and active probabilistic approaches
No full text
An efficient similarity metric for omnidirectional vision sensors
No full textThis paper presents an efficient metric for the computation of the similarity among omnidirectional images (image matching). The representation of image appearance is based on feature vectors that include both the chromatic attributes of color sets and their mutual spatial relationships. The proposed metric fits well to robotic navigation using omnidirectional vision sensors, because it has very important properties: it is reflexive, compositional and invariant with respect to image scaling and rotation. The robustness of the metric was repeatedly tested using omnidirectional images for a robot localization task in a real indoor environment
System for real-time verification and detection of stock shortages of goods displayed for sale
No full textMetodo per la determinazione della quantità e della tipologia dei rifiuti prodotti da un dato soggetto produttore e sistema di raccolta e smaltimento che attua tale metodo
No full textAppearance-based robotics - Robot localization in partially explored environments
No full textRobot 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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