Hardware-Accelerated Mars Sample Localization Via Deep Transfer Learning From Photorealistic Simulations

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...

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Bibliographic Details
Published in:	IEEE robotics and automation letters Vol. 7; no. 4; pp. 12555 - 12561
Main Authors:	Castilla-Arquillo, Raul, Perez-del-Pulgar, Carlos, Paz-Delgado, Gonzalo Jesus, Gerdes, Levin
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.10.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Artificial neural networks Computer architecture Computer vision Datasets Deep learning for visual perception Electron tubes Feature extraction Hardware hardware-software integration in robotics Laboratory tests Localization Location awareness Machine learning Mars Mars rovers Mars sample return missions Mars surface Pose estimation RGB-D perception space robotics and automation Test stands Transfer learning Tubes
ISSN:	2377-3766, 2377-3766
Online Access:	Get full text
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