Deep learning based speed estimation for constraining strapdown inertial navigation on smartphones

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Cortes Reina, Santiago
dc.contributor.author Solin, Arno
dc.contributor.author Kannala, Juho
dc.date.accessioned 2018-12-10T10:22:08Z
dc.date.available 2018-12-10T10:22:08Z
dc.date.issued 2018
dc.identifier.citation Cortes Reina , S , Solin , A & Kannala , J 2018 , Deep learning based speed estimation for constraining strapdown inertial navigation on smartphones . in 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP) . Institute of Electrical and Electronics Engineers , Aalborg , pp. 1-6 , IEEE International Workshop on Machine Learning for Signal Processing , Aalborg , Denmark , 17/09/2018 . DOI: 10.1109/MLSP.2018.8516710 en
dc.identifier.isbn 978-1-5386-5477-4
dc.identifier.other PURE UUID: 8308953e-4384-4a8c-99e1-ff01407df121
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/deep-learning-based-speed-estimation-for-constraining-strapdown-inertial-navigation-on-smartphones(8308953e-4384-4a8c-99e1-ff01407df121).html
dc.identifier.other PURE LINK: https://arxiv.org/abs/1808.03485
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/30201883/1808.03485.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/35128
dc.description.abstract Strapdown inertial navigation systems are sensitive to the quality of the data provided by the accelerometer and gyroscope. Low-grade IMUs in handheld smart-devices pose a problem for inertial odometry on these devices. We propose a scheme for constraining the inertial odometry problem by complementing non-linear state estimation by a CNN-based deep-learning model for inferring the momentary speed based on a window of IMU samples. We show the feasibility of the model using a wide range of data from an iPhone, and present proof-of-concept results for how the model can be combined with an inertial navigation system for three-dimensional inertial navigation. en
dc.format.extent 1-6
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartof IEEE International Workshop on Machine Learning for Signal Processing en
dc.relation.ispartofseries 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP) en
dc.rights openAccess en
dc.subject.other 113 Computer and information sciences en
dc.title Deep learning based speed estimation for constraining strapdown inertial navigation on smartphones en
dc.type A4 Artikkeli konferenssijulkaisussa fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Computer Science
dc.contributor.department Professorship Solin A.
dc.contributor.department Professorship Kannala J.
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201812106143
dc.identifier.doi 10.1109/MLSP.2018.8516710
dc.type.version acceptedVersion


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