A Study on Disturbance Classification of Unmanned Vehicle Data Using SVMSVM을 이용한 무인이동체의 외란 분류 기법 연구

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.In this paper, we present disturbance classification from unmanned vehicle data using a support vector machine (SVM). Disturbances that occur while operating unmanned vehicles are classified into various categories. We considered a problem in which the unmanned vehicle was a quadrotor model, and the type of operation data that could be used to classify disturbances well was selected by considering the characteristics of the model. Time series data of unmanned vehicle operation are not suitable for solving using SVM, necessitating the extraction of statistical features from time series data that can be well classified. Accordingly, we modeled a quadrotor and various disturbances to investigate unmanned vehicle disturbance classification using an SVM with selected statistical features. Experiments show that the statistical features and SVM can classify the disturbances well.
Publisher
Institute of Control, Robotics and Systems
Issue Date
2022-04
Language
English
Article Type
Article
Citation

Journal of Institute of Control, Robotics and Systems, v.28, no.4, pp.304 - 312

ISSN
1976-5622
DOI
10.5302/J.ICROS.2022.21.0190
URI
http://hdl.handle.net/10203/296538
Appears in Collection
AE-Journal Papers(저널논문)
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