Abstract
The multi-sensor artificial lateral line system (ALLS) can identify the flow-field’s parameters to realize the closed-loop control of the underwater robotic fish. An inappropriate sensor placement of ALLS may result in inaccurate flow-field parametric identification. Therefore, this paper proposes a method to optimize the sensor placement configuration of the ALLS, which mainly included three algorithms, the feature importance algorithm based on mean and variance (MVF), the feature importance algorithm based on distance evaluation (DF), and the information redundancy (IR) algorithm. The optimal sensor placement performance selected by this method is verified by simulation. In addition, further experimental verification was conducted using the ALLS. Compared with the uniform sensor placement configuration mentioned in recent studies, the experimental results suggest that the optimal sensor placement method can achieve a more effective prediction of the flow-field parameters, therefore strengthening the underwater robotic fish’s perception and control function.
Highlights
Through the optimal sensor placement algorithm, we can achieve multiple sensor placement design by changing three weight factors that correspond to the feature importance algorithm based on mean and variance (MVF), the feature importance algorithm based on distance evaluation (DF), and the information redundancy (IR) algorithm
The sensor placement of the artificial lateral line system (ALLS) has a significant influence on flow parametric recognition
An inappropriate sensor placement may result in information loss or redundancy, leading to mistakes in flow parametric recognition
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. The lateral line is a collection of sense organs involved in various fish behaviors, such as prey detection, predator avoidance, schooling, intraspecific communication, rheotaxis, station holding, etc. The biological lateral line’s sensing unit is the neuromast [4], including superficial neuromasts (SNs) and canal neuromasts (CNs). The SNs stick out of the fish skin [5] and respond to flow velocity [6]. CNs are distributed on both sides of the fish body at the same horizontal level [7] and are sensitive to the orientation [6]
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