Distributed Robust Vehicle State Estimation

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dc.contributor.authorHashemi, Ehsan
dc.contributor.authorPirani, Mohammad
dc.contributor.authorFidan, Baris
dc.contributor.authorKhajepour, Amir
dc.contributor.authorChen, Shih-Ken
dc.contributor.authorLitkouhi, Baktiar
dc.date.accessioned2017-12-15T17:49:34Z
dc.date.available2017-12-15T17:49:34Z
dc.date.issued2017-06
dc.description© IEEE 2017. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.description.abstractA distributed estimation approach based on opinion dynamics is proposed to enhance the reliability of vehicle corners’ velocity estimates, which are obtained by an unscented Kalman filter. The corners’ estimates from a Kalman observer, which is formed by integrating the model-based and kinematic-based velocity estimation approaches, are utilized as opinions with different levels of confidence in the developed algorithm. More reliable estimates robust to disturbances and time delay are achieved via solving a convex optimization problem. Road tests confirm the robustness of the methods independent of the powertrain configuration on surfaces with various friction conditions in pure and combined-slip maneuvers, which are arduous for the current vehicle state estimators.en
dc.description.sponsorshipAutomotive Partnership Canada [APCPJ 395996-09] Ontario Research Fund [ORF-RE-04-039] General Motors Co.en
dc.identifier.urihttps://doi.org/10.1109/IVS.2017.7995798
dc.identifier.urihttp://hdl.handle.net/10012/12731
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineersen
dc.subjectOpinion dynamicsen
dc.subjectDistributed estimationen
dc.subjectUnscented Kalman filteren
dc.subjectRobust observer designen
dc.titleDistributed Robust Vehicle State Estimationen
dc.typeConference Paperen
dcterms.bibliographicCitationE. Hashemi, M. Pirani, B. Fidan, A. Khajepour, S-K Chen, and B. Litkouhi, "Distributed Robust Vehicle State Estimation", in Proc. of IEEE Intelligent Vehicles Symposium, CA, USA, 2017.en
uws.contributor.affiliation1Faculty of Engineeringen
uws.contributor.affiliation2Mechanical and Mechatronics Engineeringen
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen
uws.typeOfResourceTexten

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