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Artificial Lateral Line Technology by Martha - Friday, August 24, 2012, 01:15 AM Lateral Line in Fish Inspires Artificial Sensors in Underwater Vessels Fish are able to orient themselves in currents, identify “home” territory, and identify and locate predators or prey underwater in even very low visibility due in large part to the lateral line of sensors that runs down the center of their bodies. This lateral line is found in all fish species from the smallest gobies to the largest whale sharks. The line is composed of millions of hair-like sensors associated with nerves. The hairs, stimulated by movement in the water, trigger nerves that send complex signals about the environment to the fish. More specifically, the lateral line is visible along the side of most fish. Rather than being a physical or solid line, the structure is composed of millions of closely placed hair assemblies. Each individual sensor hair is surrounded by a corresponding set of hairs that create a sort of bristle assembly within the pore structure. The action of the water on each of the primary and corresponding hairs at a given site provides information about movement in the water. Water moving from different directions will interact with the corresponding hairs differently, providing evidence to that site of the direction of movement. As the brain assembles information from the millions of cells along the lateral line, clear information can be developed about what is in the water, where it is, and what movement it makes (Webb, Montgomery, and Modgens, 2008; Yamanaka, Masanori, Fukuda, & Sasaki, 2010).. Fish cannot be said to “make sense” of this data but rather their brains are able to sort and monitor the influx of information to analyze the environment around them. This occurs on a level of speed and sensitivity comparable to that by which humans sort the mountains of information they have incoming such as the surfaces on which they sit, the clothing that touches their body, background noise and danger signals to identify information important for the survival. The lateral line is so sensitive that it is capable of discerning movement in the immediate area from that in the background or distance (Klein & Bleckmann, 2012). For this reason, it is impossible to sneak up on a fish from behind despite the fact that their eyes are poorly located for a prey species. Likewise, the lateral line enables fish to maintain school structures and detect interlopers to their school structure, in most cases (Partridge, & Pitcher, 1980). There are some fish that are able to masquerade as school members or shadow other fish species but the evolution of these behaviors is quite elaborate and advanced. Borrowing from this ability, researchers have been working to develop artificial lateral line sensor capability for underwater robots. Researchers at the Technical University in Munich (TUM) Germany have developed mechanical sensors inspired by the hair/nerve component of fish lateral lines and implanted that technology in the robot, Snookie (no relation to the New Jersey pseudo-celebrity) (Franosch, Sosnowski, Chami, Kuhnlenz, Hirchet, & van Hememen, 2010). The artificial sensors are thermistors – ceramic or polymer sensors that react to specific variances in temperature to open or close circuits, converting temperature signals into electrical impulses. These impulses are managed or monitored by remote or tethered computers that operate on the information. A single TUM project thermistor is only 0.36mm. Rows of these thermistors can be arranged along the sides of Underwater Remote Operated Vehicles (UROV) to provide more sophisticated information about UROV position, orientation, and environment than was previously possible. Someday, nanotechnology may make it possible to create thermistors at a much smaller scale, such as that shown below. Applications for such nanothermistors is limitless. Photo courtesy of http://www.gizmag.com/researchers-create-lateral-linesensors/14141/picture/110314/ References Akanyeti, O.,, Fiazza, C., & Fiorini, P. (2010). Attentional mechanisms for lateral line sensing through spectral analysis. Lecture Notes in Computer Science, 6226(From Animals to Animats, 11)252-262. Coombs, S. (2001). Smart skins: Information processing by lateral line flow sensors. Autonomous Robots, 11(3) 255-261. Franosch, J.M.P., Sosnowski, S., Chami, N.K., Kuhnlenz, K., Hirchet, S., & van Hememen, J. L. (2010). Biomimetic lateral-line system for underwater vehicles. Retrieved from http://www.t35.ph.tum.de/addons/publications/Franosch-2010.pdf Klein, A.T., & Bleckmann, H. (2012). Lateral line canal morphology and noise reduction. The Effect of Noise on Aquatic Life: Advances in Experimental Medicine and Biology, 730 (Part II) 121-123. DOI: 10.1007/978-1-4419-7311-5_27. Montgomery, J.C., Coombs, S., & Baker, C.F. (2001). The mechanosensory lateral line system of the hypogean forms of. Environmental Biology of Fishes, 62(1-3) 87-96. Partridge, B.L., & Pitcher, T.J. (1980). The sensory basis of fish schools: Relative roles of lateral lines and vision. Journal of comparative Physiology A: Neurothology, Sensory, Neural, and Behavioral Physiology, 135(4)315-325. Qualtieri, A.; Rizzi, F.; Todaro, M.T.; Passaseo, A.; Cingolani, R.; De Vittorio, M. (2011). Stress-driven AlN cantilever-based flow sensor for fish lateral line system. Microelectronic Engineering, 88(8)23762378. DOI: 10.1016/j.mee.2011.02.091. Webb, J.F., Montgomery, J.C., and Mogdans, J. (2008). Bioaccustics and the lateral line in fish. In, Webb, J.F., Fey, R.R., and Popper, A.N. (Eds.). Springer Handbook of Auditory Research, 1, 32, (Fish Bioacoustics)145-182. Yang, Y., Chen, J., Engel, J., Pandya, S., Chen, N., Tucker, C., Coombs, S., Jones, D.L., & Chang, L. (2006). Distant touch hydrodynamic imaging with an artificial lateral line. Proceedings of the National Academy of Sciences,103(50)18891-18895. DOI:10.1073/pnas.0609274103.