Assessing flow for sightless underwater surveillance
Despite not being able to see, the blind cave fish Astyanax fasciatus can swim at extremely high speeds without colliding with underwater objects: see Figure 1(a).1,2 Researchers believe the fish's lateral line—rows of biological microsensors that detect the pressure gradient of flows around the body—helps the fish to maneuver in complex fluid environments by generating a 3D hydrodynamic map of its surroundings: see Figure 1(b). The utility of the fish's mechanical sensing system has inspired researchers to engineer artificial lateral lines in the laboratory that mimic the structural and functional features of the fish's sensors.
Artificial lateral lines could be used to improve the navigational accuracy and efficiency of underwater vehicles in harsh, cluttered, and murky environments when sonar and vision systems are ineffective. There have been many approaches to developing such bio-inspired sensors, but most have not been capable of measuring the flows surrounding an underwater vehicle, while also being low power, low cost, small, and robust enough to withstand harsh seawater environments.
Inspired by the fish's mechanosensory abilities, we have developed flexible and self-powered arrays of micro- electromechanical system (MEMS) microsensors, capable of object tracking and shape recognition, with sensing abilities that rival those demonstrated by the fish. MEMS devices offer high resolution and high sensitivity, while making it possible to easily fabricate dense arrays of pressure sensors in a small area. We have also developed sensors made of a nanofiber scaffold covered in a hydrogel polymer. These sensors closely resemble the microstructural features the blind cave fish use to detect obstacles, avoid predators, and localize prey.
To create the flexible sensor array, we packaged piezo-electric sensors into arrays on a flexible liquid crystal polymer (LCP) substrate that could endure the harsh underwater environment: see Figure 2. While densely packed arrays of sensors could be fabricated on a silicon substrate, silicon is brittle and does not exhibit the chemical and sealing robustness needed for an underwater setting. We pre-calibrated the individual lead zirconate titanate sensors in the laboratory to determine their response to various flows before field testing. After thoroughly characterizing the sensors, we attached the arrays to a kayak. We rowed the kayak across a reservoir in various patterns to evaluate the response of the sensors to different flow conditions. These experimental tests showed that the sensors could detect flow pressures with high sensitivity and without any external power or signal post-processing.
Next, we investigated the intricate biology of the blind cave fish's sensory system to develop a materials-based approach for MEMS flow sensors capable of air- and water-flow sensing. The fish's lateral line comprises individual sensor elements called superficial neuromasts, which are standing cylindrical structures that contain mechanosensing hair cells encapsulated in a soft polymer-like material called cupula. The cupula also consists of numerous encapsulated cupular fibrils that mechanically support the cupula and play a role in transmitting energy to the embedded hair cells. The cupula, which has a low Young's modulus of 10–100Pa, bends in response to changes in flow and the embedded hair cells generate electric impulses that are sent to the fish's brain. The large surface area of the cupula enhances the overall drag on the hair cells.
To mimic the blind cave fish's lateral line, we created biomimetic hair cells on LCP membranes patterned with metal piezoresistors as sensing elements.3, 4 We developed a hydrogel cupula with biomechanical properties similar to the biological cupula on the hair cell: see Figure 3(a). We used fabrication techniques such as electrospinning to deposit fibers on the hair cell, which acted as a scaffold to support the soft hydrogel material: see Figure 3(b). Experiments showed that the hydrogel material enhanced the sensitivity of the sensor. We also observed a mechanical high-pass filtering effect from the biomimetic cupula that significantly increased the accuracy of the flow sensors.
Although the lateral line is a biological sensory organ of the blind cave fish, its abilities, when translated into an artificially engineered sensing system, can enhance underwater vehicle capabilities. The arrays we developed can equip underwater vehicles with object detection, navigation, and flow sensing abilities. Future work will include developing arrays of the biomimetic sensors and creating sensors inspired by the canal neuromasts of the blind cave fish's lateral line. Unlike superficial neuromasts located externally on the surface of the body, the canal neuromast system exists under the skin and responds to pressure variations.
Nanyang Technological University
Jianmin Miao received masters-level and doctoral degrees in engineering from Darmstadt University of Technology, Germany, specializing in MEMS. He joined Nanyang Technological University in 1998 and is currently an associate professor.
Ajay Giri Prakash Kottapalli received his MS degree in photonics in 2007 and then obtained an MTech degree in solid state technology from the Indian Institute of Technology, Madras, India. He is currently a PhD student participating in the Singapore-MIT Alliance for Research and Technology (SMART) graduate fellowship program.
Mohsen Asadnia is a research associate who works with the SMART program. His research interests include MEMS devices for sensing in harsh environments, material characterization, and biomimetic and bio-inspired MEMS devices.
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Department of Mechanical Engineering
Massachusetts Institute of Technology (MIT)
Michael Triantafyllou obtained a diploma in naval architecture and marine engineering from the National Technical University of Athens in 1974. He then obtained MS degrees in ocean engineering and mechanical engineering from MIT in 1977 and an ScD in ocean engineering from MIT in 1979. He subsequently joined the MIT faculty as an assistant professor and is currently the William I. Koch Professor of Marine Technology and director of the Center for Ocean Engineering. His research interests include biomimetic robotics, flow-structure interaction and vorticity control, and dynamics and controls of marine vehicles and structures.
