Sensory systems in nature, such as flow sensors, vision sensors, acoustic sensor, etc. are characterized by extreme efficiency, small size, high sensitivity and high throughput, by far exceeding the performance of man-made sensors. In numerous biological species, hair-likestructures and cells provide flow sensory functions. In fish these structures are called lateral line neuromasts which consist of up to several hundreds or even thousands of mechanosensitive hair cells, enveloped in a gelatinous cupula and placed along the fish body.We studied an innovative biomimetic stress-driven micro-electromechanical system (MEMS) for underwater applications whose technological development is based on a silicon-based bilayer design as an Artificial Hair Cell (AHC). Waterproofing is then achieved by parylene conformal coating for underwater operation.
An array of close AHC sensors, i.e. an artificial lateral line, has been installed on fish robots to calculate orientation and velocity information to be used as input for the vehicle's control algorithm, mimicking the lateral line neuromasts along the body of real fishes. Equipping an artificial system, like underwater vehicles and fish robot, with this very close to nature data acquisition system could allow navigation through complex and harsh environments with higher propulsion efficiency and stability in the presence of turbulent flows.
Relevant CBN papers on this highlight:
- European Patent submitted no. ITTO201000748: "Stress-driven piezoelectric and piezoresistive cantilever-based micro-electro-mechanical Artificial Hair Cell electro-active device." A. Qualtieri, F. Rizzi et al.
- "Stress-driven AlN cantilever-based flow sensor for fish lateral line system" A. Qualtieri, F. Rizzi, et al., Microelectronic Engineering 88 (2011) 2376–2378.
- "Parylene-coated bioinspired artificial hair cell for liquid flow sensing" A. Qualtieri, F. Rizzi, G. Epifani, A. Ernits, M. Kruusmaa, M. De Vittorio, in press to "Microelectronic Engineering".
- "Bio-inspired artificial hair cell for flow detection" F. Rizzi, A. Qualtieri, L. Chambers, W. Megill, M. De Vittorio, International Bionic Engineering Conference 2011.