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A Generalized Reduced-Complexity Inertial Navigation System for Unmanned Aerial Vehicles
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-5735-5484
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0003-0126-1897
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-0079-9049
Number of Authors: 32017 (English)In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 25, no 1, p. 192-207Article in journal (Refereed) Published
Abstract [en]

In this paper, a generic approach to attitude and position estimation, suited for any type of unmanned aerial vehicle, is presented. This will be achieved by establishing a generic framework, which can be extended using adaptive methods to determine the thrust properties of the engines and the mass of the aircraft, while keeping the overall computational complexity of the system low. Furthermore, the effect of magnetic disturbances will be reduced in a novel way by confining the magnetic errors to affect only heading, without compromising the pitch and roll estimation of the system with error-based estimation. The efficacy of the proposed framework will be evaluated through extended simulations and experimental validations on a multirotor. Finally, guidelines will be provided toward: 1) an implementation with a reduced computational complexity and 2) the utilization of the square-root formulations of the extended Kalman filter for extending the dynamic range of the filter.  

Place, publisher, year, edition, pages
IEEE, 2017. Vol. 25, no 1, p. 192-207
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-15975DOI: 10.1109/TCST.2016.2542022ISI: 000391498700016Scopus ID: 2-s2.0-84963657298Local ID: f8f7825a-d3c5-4ac9-9ccc-5fa1819c5264OAI: oai:DiVA.org:ltu-15975DiVA, id: diva2:988951
Projects
Collaborative Aerial Robotic Workers, AEROWORKS
Funder
EU, Horizon 2020, 644128
Note

Validerad; 2017; Nivå 2; 2017-02-10 (andbra)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-09-14Bibliographically approved

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Fresk, EmilNikolakopoulos, GeorgeGustafsson, Thomas

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