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The success of mobile robots, and particularly of those interfacing with humans in daily environments (e.g., assistant robots), relies on the ability to manipulate information beyond simple spatial relations. We are interested in semantic information, which gives meaning to spatial information like images or geometric maps. We present a multi-hierarchical(More)
We describe a new technique for landmark-based self-localization which is suitable for robots with poor odom-etry. This technique uses fuzzy logic to account for errors and imprecision in visual recognition, and for extreme uncertainty in the estimate of the robot's motion. It only requires an approximate model of the sensor system and a qualitative(More)
Autonomous robots typically rely on internal representations of the environment, or maps, to plan and execute their tasks. Several types of maps have been proposed in the literature, and there is general consensus that different types have different advantages and limitations, and that each type is more suited to certain tasks and less to others. Because of(More)
The use of a symbolic model of the spatial environment becomes crucial for a mobile robot that is intended to operate optimally and intelligently in indoor scenarios. Constructing such a model involves important problems that are not solved completely at present. One is called anchoring, which implies to maintain a correct dynamic correspondence between the(More)
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