DeepLO: Multi-projection deep LIDAR odometry for space orbital robotics rendezvous relative navigation

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dc.contributor.authorKechagias-Stamatis, Odysseas
dc.contributor.authorAouf, Nabil
dc.contributor.authorDubanchet, Vincent
dc.contributor.authorRichardson, Mark A.
dc.date.accessioned2020-09-17T14:39:37Z
dc.date.available2020-09-17T14:39:37Z
dc.date.freetoread2021-07-31
dc.date.issued2020-07-30
dc.description.abstractThis work proposes a new Light Detection and Ranging (LIDAR) based navigation architecture that is appropriate for uncooperative relative robotic space navigation applications. In contrast to current solutions that exploit 3D LIDAR data, our architecture suggests a Deep Recurrent Convolutional Neural Network (DRCNN) that exploits multi-projected imagery of the acquired 3D LIDAR data. Advantages of the proposed DRCNN are; an effective feature representation facilitated by the Convolutional Neural Network module within DRCNN, a robust modeling of the navigation dynamics due to the Recurrent Neural Network incorporated in the DRCNN, and a low processing time. Our trials evaluate several current state-of-the-art space navigation methods on various simulated but credible scenarios that involve a satellite model developed by Thales Alenia Space (France). Additionally, we evaluate real satellite LIDAR data acquired in our lab. Results demonstrate that the proposed architecture, although trained solely on simulated data, is highly adaptable and is more appealing compared to current algorithms on both simulated and real LIDAR data scenarios affording better odometry accuracy at lower computational requirements.en_UK
dc.identifier.citationKechagias-Stamatis O, Aouf N, Dubanchet V, Richardson M. (2020) DeepLO: Multi-projection deep LIDAR odometry for space orbital robotics rendezvous relative navigation. Acta Astronautica, Volume 177, December 2020, pp. 270-285en_UK
dc.identifier.cris27832402
dc.identifier.issn0094-5765
dc.identifier.urihttps://doi.org/10.1016/j.actaastro.2020.07.034
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/15811
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectConvolutional neural networksen_UK
dc.subjectDeep learningen_UK
dc.subjectLIDARen_UK
dc.subjectMulti-dimensional processingen_UK
dc.subjectRecurrent neural networksen_UK
dc.subjectRelative navigationen_UK
dc.subjectRoboticsen_UK
dc.titleDeepLO: Multi-projection deep LIDAR odometry for space orbital robotics rendezvous relative navigationen_UK
dc.typeArticleen_UK

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