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des algorithmes d'apprentissage automatique (IA et Machine Learning) pour prendre en compte les phénomènes de dérives et permettre l'auto calibration des mesures
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artificielle, en particulier des algorithmes d'apprentissage profonds, nous obtenons des modalités de plus haut niveau liées à l'actimétrie : la vitesse de déplacements voire certains mouvements corporels. Les
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, including cellular and Wi-Fi networks, in order to meet the requirements of emerging critical applications. In this context, intelligent embedded devices (augmented cameras, connected sensors) generate
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: The objective of this task is to develop a decision-support model to assist in the selection of diagnostic and prognostic algorithms by jointly optimizing energy and computational costs. Two goals are pursued: (i
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, algorithms must respond in real time and use partial sensor data of varying quality. In addition, I made the decision to focus only on embedded systems, depriving robots of internet connectivity and the myriad
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integrating artificial intelligence, from algorithm design to on-sky demonstration. The objective is to design intelligent adaptive optics systems capable of correcting sensor nonlinearities, anticipating
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RF information and limited communication. A key contribution of the project is the design of frugal embedded control algorithms tailored to resource-constrained robotic platforms. These control
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mobility and vulnerability to falls. The project will combine physiological sensory biomarkers with postural control, gait analysis and real-life mobility measurements obtained using wearable sensors and
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of simulated sensors (vision, sonar, LiDAR, inertial navigation). - Implementation of guidance, control, and planning algorithms under environmental constraints. - Implementation of distributed simulation