Title :
Underwater source localization using an IPMC-based artificial lateral line
Author :
Abdulsadda, Ahmad T. ; Tan, Xiaobo
Author_Institution :
Dept. of Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI, USA
Abstract :
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 navigation. In 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 network. The effectiveness of the proposed lateral line was validated in localization of underwater motion sources, including both a vibrating sphere (a dipole source) and a flapping foil. In particular, as a proof of concept, a prototype with Body Length (BL) of 8 cm, comprising five millimeter-scale IPMC sensors, was constructed and tested. Experimental results showed that the IPMC-based lateral line could localize the sources from 4-5 BLs away, with a localization error comparable to source placement resolution at the source sensor separation of 1 BL. In addition to the ease of fabrication, these results established the competitiveness of the proposed approach, in terms of both localization range and accuracy, against the state of the art in artificial lateral lines.
Keywords :
composite materials; electroactive polymer actuators; geophysical signal processing; mobile robots; neural nets; sensors; source separation; underwater vehicles; IPMC-based artificial lateral line; aquatic amphibian; bioinspired artificial lateral line system; body length; fish; ionic polymer-metal composites; lateral line system; localization error; millimeter-scale IPMC sensor; neural network; prey-predator detection; sensory organ; source placement resolution; source-sensor separation; underwater motion source localization; underwater robots; underwater vehicles; Biology; Fabrication; Robot sensing systems; Sensor arrays; Training;
Conference_Titel :
Robotics and Automation (ICRA), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-386-5
DOI :
10.1109/ICRA.2011.5980545