An artificial lateral line system using IPMC sensor arrays

作     者：Ahmad T.Abdulsadda Xiaobo Tan 

作者机构：Smart Microsystems LaboratoryDepartment of Electrical and Computer EngineeringMichigan State UniversityEast LansingMI 48824 USA January 92012 

出 版 物：《International Journal of Smart and Nano Materials》 (国际智能和纳米材料杂志（英文）)

年 卷 期：2012年第3卷第3期

页      面：226-242页

核心收录：

学科分类：08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 080502[工学-材料学] 0813[工学-建筑学] 0814[工学-土木工程] 0801[工学-力学（可授工学、理学学位）] 0702[理学-物理学] 

基　　金：supported in part by the National Science Foundation(ECCS 0547131,CCF 0820220,IIS 0916720) the Office of Naval Research(Grant N000140810640) 

主　　题：ionic polymer-metal composite(IPMC) lateral line system neural networks flow sensing dipole source localization 

摘      要：Most fish and aquatic amphibians use the lateral line system,consisting of arrays of hair-like neuromasts,as an important sensory organ for prey/predator detection,communication,and *** this paper a novel bio-inspired artificial lateral line system is proposed for underwater robots and vehicles by exploiting the inherent sensing capability of ionic polymer-metal composites(IPMCs).Analogous to its biological counterpart,the IPMC-based lateral line processes the sensor signals through a neural *** effectiveness of the proposed lateral line is validated experimentally in the localization of a dipole source(vibrating sphere)*** particular,as a proof of concept,a prototype with body length(BL)of 10 cm,comprising six millimeter-scale IPMC sensors,is constructed and *** results have shown that the IPMC-based lateral line can localize the source from 1-2 BLs away,with a maximum localization error of 0.3 cm,when the data for training the neural network are collected from a grid of 2 cm by 2 cm *** effect of the number of sensors on the localization accuracy has also been examined.