A simulation-to-real navigation policy enables a quadrotor to locate an odor source using only basic olfaction sensors and optional vision, validated in indoor real-world flights.
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Self-supervised GNN reduces average voltage violations when post-processing forecasts on the full-scale French HV-EHV grid.
Reinforcement learning is used to learn adaptive policies for selecting parameters in nonlinear Bayesian filters, improving estimate quality and consistency in experiments with the unscented Kalman filter and stochastic integration filter.
citing papers explorer
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Chasing Ghosts: A Simulation-to-Real Olfactory Navigation Stack with Optional Vision Augmentation
A simulation-to-real navigation policy enables a quadrotor to locate an odor source using only basic olfaction sensors and optional vision, validated in indoor real-world flights.
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Self-Supervised Graph Neural Networks for Full-Scale Tertiary Voltage Control
Self-supervised GNN reduces average voltage violations when post-processing forecasts on the full-scale French HV-EHV grid.
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Learning Adaptive Parameter Policies for Nonlinear Bayesian Filtering
Reinforcement learning is used to learn adaptive policies for selecting parameters in nonlinear Bayesian filters, improving estimate quality and consistency in experiments with the unscented Kalman filter and stochastic integration filter.