Dynamic System Identification of Underwater Vehicles Using Multi-Output Gaussian Processes
نویسندگان
چکیده
Non-parametric system identification with Gaussian Processes for underwater vehicles is explored in this research the purpose of modelling autonomous vehicle (AUV) dynamics low amount data. Multi-output processes and its aptitude to model dynamic an underactuated AUV without losing relationships between tied outputs used. The simulation a first-principles Remus 100 employed capture data training validation multi-output processes. metric required procedure carry out 6 degrees freedom (DoF) also shown paper. are compared popular technique recurrent neural network show that manage surpass RNN non-parametric highly coupled DoF added benefit providing measurement confidence.
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ژورنال
عنوان ژورنال: International Journal of Automation and Computing
سال: 2021
ISSN: ['1751-8520', '1476-8186']
DOI: https://doi.org/10.1007/s11633-021-1308-x