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Efficient and responsible fault detection in AUVs: SHAP-Interpretable cubic SVM on time-series data

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Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, Ahead of Print.
Fault detection in Autonomous Underwater Vehicles (AUVs) is crucial for ensuring their safe and efficient operation, especially in challenging underwater environments. In this study, we investigate traditional machine learning models to detect common AUV ...