Christophe Giovannangeli

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— This article presents an efficient and mature vision-based navigation algorithm based on a sensory-motor learning. Neither Cartesian nor topological map is required, but a set of biologically inspired place cells. Each place cell defines a location by a spatial constellation of online learned landmarks. Their activity provides an internal measure of(More)
— We address in this paper the problem of the autonomous online learning of a sensory-motor task, demonstrated by an operator guiding the robot. For the last decade, we have developed a vision-based architecture for mobile robot navigation. Our bio-inspired model of the navigation has already proved to achieve sensory-motor tasks in real time both in(More)
We present a navigation and planning system using vision for extracting non predefined landmarks, a dead-reckoning system generating the integrated movement and a topological map. Localisation and planning remain possible even if the map is partially unknown. An om-nidirectional camera gives a panoramic images from which unpredefined landmarks are(More)
A wide variety of visual recognition systems are developed for precise tasks and types of objects. In this paper we would like to emphasize ways to build a more generic recognition system. Perception is one of these mechanisms that psychologists particularly pointed out as a fundamental one for actively organizing and making sense of input sensory(More)
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