Hybrid, metric - topological, mobile robot navigation
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In this paper the metric and topological paradigms are integrated in a hybrid system for both localization and map building. A global topological map connects local metric maps, allowing a compact environment model, which does not require global metric con ...
The Autonomous Systems Lab at the Swiss Federal Institute of Technology Lausanne (EPFL) is engaged in mobile robotics research. The labs research focuses mainly on indoor localization and map building, outdoor locomotion and navigation, and micro mobile r ...
In this paper a new localization approach combining the metric and topological paradigm is presented. The main idea is to connect local metric maps by means of a global topological map. This allows a compact environment model which does not require global ...
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In this paper a hierarchical multi-resolution approach allowing for high precision and distinctiveness is presented. The method combines topological and metric paradigm. The metric approach, based on the Kalman Filter, uses a new concept to avoid the probl ...
Mobile robot localization deals with uncertain sensory information as well as uncertain data association. In this paper we present a probabilistic feature-based approach to global localization and pose tracking which explicitly addresses both problems. Loc ...
In this paper simultaneous localization and map building is performed with a hybrid, metric - topological, approach. A global topological map connects local metric maps, allowing a compact environment model, which does not require global metric consistency ...