Autonomous Reinforcement Control of Visual Underwater Vehicles: Real-Time Experiments Using Computer Vision
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DOI: 10.1109/tvt.2022.3177596
Abstract: Swift decision-making based on visual environment perception is crucial for autonomous control of visual underwater vehicles (VUVs) during underwater missions. However, learning perception and decision models individually might result in weak robustness of overall control… read more here.
Keywords: network; reinforcement; reinforcement control; control ... See more keywords