Failure mode analysis (FMA) for visual-based navigation for UAVs in urban environment

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dc.contributor.authorTabassum, Tarafder Elmi
dc.contributor.authorPetrunin, Ivan
dc.contributor.authorRana, Zeeshan
dc.date.accessioned2022-11-24T14:51:41Z
dc.date.available2022-11-24T14:51:41Z
dc.date.issued2022-08-26
dc.description.abstractVisual-based navigation systems for Unmanned Aerial vehicles (UAVs) have become an interesting research area focused on improving robustness and accuracy in the urban environment. However, a lack of integrity can damage UAVs, limiting their potential usage in civil applications. For safety reasons, integrity performance requirements must be met. In literature, such systems require significant attention for their ability to perform fault analysis, referred to as failure mode. In this paper, we have conducted a failure mode analysis in urban environments for UAVs to identify threats and faults presented in existing Visual-inertial Navigation Systems. In addition, we propose a federated-filter-based fault detection and execution system to improve navigation performance under faulted conditions.en_UK
dc.identifier.citationTabassum TE, Petrunin I, Rana Z. (2022) Failure mode analysis (FMA) for visual-based navigation for UAVs in urban environment. In: UK-RAS22 5th UK Robotics and Autonomous Systems Conference, 26 August 2022, Aberystwyth, Wales, UKen_UK
dc.identifier.urihttps://doi.org/10.31256/Mx7Zx4J
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18739
dc.language.isoenen_UK
dc.publisherUK-Robotics and Autonomous Systems (UK-RAS) Networken_UK
dc.rights© Cranfield University, 2015. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectvisual-based navigationen_UK
dc.subjectintegrityen_UK
dc.subjectfailure mode analysisen_UK
dc.subjecturban environmenten_UK
dc.subjectGNSSen_UK
dc.titleFailure mode analysis (FMA) for visual-based navigation for UAVs in urban environmenten_UK
dc.typeConference paperen_UK

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