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Hardware-accelerated Mars Sample Localization via deep transfer learning from photorealistic simulations. (arXiv:2206.02622v2 [cs.CV] UPDATED)
Nov. 7, 2022, 2:12 a.m. | Raúl Castilla-Arquillo, Carlos Jesús Pérez-del-Pulgar, Gonzalo Jesús Paz-Delgado, Levin Gerdes
cs.LG updates on arXiv.org arxiv.org
The goal of the Mars Sample Return campaign is to collect soil samples from
the surface of Mars and return them to Earth for further study. The samples
will be acquired and stored in metal tubes by the Perseverance rover and
deposited on the Martian surface. As part of this campaign, it is expected that
the Sample Fetch Rover will be in charge of localizing and gathering up to 35
sample tubes over 150 Martian sols. Autonomous capabilities are critical …
arxiv hardware localization mars simulations transfer transfer learning
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