H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles

A Master of Science thesis in Mechatronics Engineering by Karim Diab entitled, “H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles”, submitted in April 2025. Thesis advisor is Dr. Mamoun Abdel-Hafez. Soft copy is available (Thesis, Completion Certifica...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Diab, Karim (author)
التنسيق: doctoralThesis
منشور في: 2025
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/11073/26143
الوسوم: إضافة وسم
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author Diab, Karim
author_facet Diab, Karim
author_role author
dc.contributor.none.fl_str_mv Abdel-Hafez, Mamoun
dc.creator.none.fl_str_mv Diab, Karim
dc.date.none.fl_str_mv 2025-06-19T08:03:39Z
2025-06-19T08:03:39Z
2025-04
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2025.05
https://hdl.handle.net/11073/26143
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Stochastic estimation
Kalman filter
Process noise covariance
Gaussian process regression
Stochastic differential equations
Unmanned ground vehicles
Mobile vehicles
dc.title.none.fl_str_mv H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Mechatronics Engineering by Karim Diab entitled, “H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles”, submitted in April 2025. Thesis advisor is Dr. Mamoun Abdel-Hafez. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
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oai_identifier_str oai:repository.aus.edu:11073/26143
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
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spelling H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground VehiclesDiab, KarimStochastic estimationKalman filterProcess noise covarianceGaussian process regressionStochastic differential equationsUnmanned ground vehiclesMobile vehiclesA Master of Science thesis in Mechatronics Engineering by Karim Diab entitled, “H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles”, submitted in April 2025. Thesis advisor is Dr. Mamoun Abdel-Hafez. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR)Abdel-Hafez, Mamoun2025-06-19T08:03:39Z2025-06-19T08:03:39Z2025-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2025.05https://hdl.handle.net/11073/26143en_USoai:repository.aus.edu:11073/261432025-06-26T12:27:31Z
spellingShingle H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles
Diab, Karim
Stochastic estimation
Kalman filter
Process noise covariance
Gaussian process regression
Stochastic differential equations
Unmanned ground vehicles
Mobile vehicles
status_str publishedVersion
title H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles
title_full H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles
title_fullStr H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles
title_full_unstemmed H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles
title_short H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles
title_sort H-Adaptive and Gaussian Processes Techniques for High-Accuracy State Estimation of Ground Vehicles
topic Stochastic estimation
Kalman filter
Process noise covariance
Gaussian process regression
Stochastic differential equations
Unmanned ground vehicles
Mobile vehicles
url https://hdl.handle.net/11073/26143