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approach makes it easier to identify different local optima using sampling mechanisms. In stochastic optimization, distribution estimation algorithms (EDA) are an alternative approach to traditional
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, Intelligent_Mapping is integrated into the IRIMA Plateformes Consortium, supported by BRGM (PI: J. Langlois). The primary aim of Intelligent_Mapping is to develop Artificial Intelligence (AI) algorithms able
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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
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approach based on Deep Learning algorithms will be developed and implemented to obtain additional information by coupling the recorded data. Furthermore, the increase in acquisition rates of measurement
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control algorithms that create value for multiple stakeholders, including EV users, aggregators, grid operators, and energy markets. – Develop advanced co-simulation platforms coupling distribution network
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dedicated to developing and exploring immersive experiences, novel context-aware applications, and distributed virtual environments. The lab's research focuses on immersion, interactivity, collaboration