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Correcting Learning-based Perception for Safety

Miao, Yan et al.
arXiv (All) · Papers
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computer-vision-and-pattern-recognitionrobotics
Learning-enabled perception is important in many autonomous systems. Unlike traditional sensors, the boundary where ML perception does or does not work is poorly characterized. Incorrect perception can lead to unsafe or overtly conservative downstream control actions. In this paper, we propose a two
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