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Deciphering the connection between upstream obstacles, wake structures, and root signals in seal whisker array sensing using interpretable neural networks

Authors :
Dariush Bodaghi
Yuxing Wang
Geng Liu
Dongfang Liu
Qian Xue
Xudong Zheng
Source :
Frontiers in Robotics and AI, Vol 10 (2023)
Publication Year :
2023
Publisher :
Frontiers Media S.A., 2023.

Abstract

This study presents a novel method that combines a computational fluid-structure interaction model with an interpretable deep-learning model to explore the fundamental mechanisms of seal whisker sensing. By establishing connections between crucial signal patterns, flow characteristics, and attributes of upstream obstacles, the method has the potential to enhance our understanding of the intricate sensing mechanisms. The effectiveness of the method is demonstrated through its accurate prediction of the location and orientation of a circular plate placed in front of seal whisker arrays. The model also generates temporal and spatial importance values of the signals, enabling the identification of significant temporal-spatial signal patterns crucial for the network’s predictions. These signal patterns are further correlated with flow structures, allowing for the identification of important flow features relevant for accurate prediction. The study provides insights into seal whiskers’ perception of complex underwater environments, inspiring advancements in underwater sensing technologies.

Details

Language :
English
ISSN :
22969144
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Frontiers in Robotics and AI
Publication Type :
Academic Journal
Accession number :
edsdoj.b00973802fc147f78038b3ac1030fcf0
Document Type :
article
Full Text :
https://doi.org/10.3389/frobt.2023.1231715