Web: http://arxiv.org/abs/2201.02569

Jan. 10, 2022, 2:10 a.m. | Christian Pfeiffer, Simon Wengeler, Antonio Loquercio, Davide Scaramuzza

cs.LG updates on arXiv.org arxiv.org

Humans race drones faster than neural networks trained for end-to-end
autonomous flight. This may be related to the ability of human pilots to select
task-relevant visual information effectively. This work investigates whether
neural networks capable of imitating human eye gaze behavior and attention can
improve neural network performance for the challenging task of vision-based
autonomous drone racing. We hypothesize that gaze-based attention prediction
can be an efficient mechanism for visual information selection and decision
making in a simulator-based drone racing task. We test this hypothesis using
eye gaze and flight …

agents arxiv attention autonomous performance prediction racing

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