Reference : ABSOLUTE LOCALIZATION FOR SURFACE ROBOTICS IN GPS-DENIED ENVIRONMENTS USING A NEURAL ...
Scientific congresses, symposiums and conference proceedings : Poster
Engineering, computing & technology : Aerospace & aeronautics engineering
Computational Sciences
http://hdl.handle.net/10993/45552
ABSOLUTE LOCALIZATION FOR SURFACE ROBOTICS IN GPS-DENIED ENVIRONMENTS USING A NEURAL NETWORK.
English
Wu, Ben [National Astronomical Observatory of Japan]
Ludivig, Philippe mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Potter, Ross [Brown University]
Chung, Andrew [Tensorlicious]
Seabrook, Timothy [University of Oxford]
23-Oct-2020
A4
Yes
International
i-SAIRAS 2020
from 19-10-2020 to 23-10-2020
[en] localization ; absolute ; planetary ; gps ; gps-denied
[en] Accurate localization in surface robotics is essential for navigation, path planning, and science objectives. On Earth, absolute localization can be readily achieved via satellite navigation (e.g., GPS). For other planetary bodies such as the Moon or Mars, however, such systems are unavailable. Current methods for absolute localization of planetary rovers rely on time- and labor-intensive human visual matching of surface perspective features with satellite images. Relative localization also accumulates errors over time, with different methods estimating dissimilar locations (e.g., [1]). Thus, an absolute localization method that can quickly, automatically, and accurately reduce the position search space is of great benefit to future planetary exploration missions. This project [2] presents a new approach to localizing planetary rovers: training an artificial neural network to match surfaceperspective imagery to corresponding satellite maps.
Fonds National de la Recherche - FnR
Grant 11824057
http://hdl.handle.net/10993/45552
https://www.hou.usra.edu/meetings/isairas2020/eposter/4032.pdf

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