An algorithm for data acquisition from underwater environment through artificial hair cells will allow autonomous underwater vehicles to obtain same skills of fishes.
Natural evolution has allowed the organisms to adapt to environmental conditions through a perfect symbiosis between the nervous system and sensory terminals located on their body. Fishes are, for example, equipped with two lateral lines made by deformable cilia; if subjected to a flow of water, they send information that the brain interprets as a kind of "hydrodynamic" vision.
An autonomous underwater vehicle equipped with a similar artificial system should make a quantum leap in controlling its movements in an underwater environment, where information related to the "standard" optical vision is very limited. In June, the research group coordinated by Francesco Rizzi in the Center for Bio-molecular Nanotechnologies, center of Istituto Italiano di Tecnologia (IIT-CBN@UNILE) in Lecce, has published a new multidisciplinary research work entitled "A bio-inspired real-time capable artificial lateral line system for Freestream flow measurements" in the journal "Bioinspiration & Biomimetics".
The research shows that, by applying "computer science" to micro-electro-mechanical systems (MEMS), a linear arrangement of artificial hair cells computes the speed of an air flow with an accuracy comparable with commercial sensors and with an unexpected wealth of information such as directionality, frequency and speed of propagation of a pulse stream from aerial sources. The developed "cross-correlation procedure" also allows to derive information from noise fluctuations that propagate in the chaotic motion of water and air and can be used in the robot control system. This "Artificial Lateral Line" will be applied to underwater vehicles for autonomous control system but also as portable and wearable systems for obtaining useful information for divers employed in risky underwater operations.
A bio-inspired real-time capable artificial lateral line system for freestream flow measurements
Published: 11 July 2016
IIT OpenTalk Editorial Staff