Christophe Giovannangeli

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In this paper, a model of visual place cells (PCs) based on precise neurobiological data is presented. The robustness of the model in real indoor and outdoor environments is tested. Results show that the interplay between neurobiological modelling and robotic experiments can promote the understanding of the neural structures and the achievement of robust(More)
In this paper, we present a model for the generation of grid cells and the emergence of place cells from multimodal input to the entorhinal cortex (EC). In this model, grid cell activity in the dorsocaudal medial entorhinal cortex (dMEC) [28] results from the operation of a long-distance path integration system located outside the hippocampal formation,(More)
This article presents an efficient and mature vision-based navigation algorithm based on sensory-motor learning. Neither Cartesian nor topological map are 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)
This article presents a bio-inspired neural network providing planning capabilities in autonomous navigation applications. The proposed architecture (hippocampus model) learns, recognizes and predicts transitions between places for any system able to provide a localization gradient from the current position to each learned place. The recurrent synapses of a(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)
— For the last decade, we have developed a bio-inspired control architecture for the autonomous navigation of mobile robots. The robot is able to learn to reproduce a homing or a route following behavior by interacting with a human teacher. However, the system strongly relies on the estimation of the orientation provided by a magnetic compass. We propose in(More)
In this paper, we will incrementally build a complete pursuit algorithm to deal with a 2-players PEG in presence of a single unknown convex obstacle. We will first provide a sufficient condition to achieve capture without disappearance. Then, we will solve the circular obstacle problem, a particular problem highlighting a necessary trade-off between(More)