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1.2: Motivation for this multidisciplinary study

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  • 1.2 Motivation for this multidisciplinary study

    So, why a special electrical engineering course focused on biologically-inspired sensory system designs and signal processing techniques? A few of the reasons include:

    - Natural systems solve engineering problems

    - Biological information is becoming increasingly more available

    - Technology is becoming increasingly more affordable and available

    - Research agencies continue to support bio-inspiration

    - A better understanding of biology can result from attempting to imitate biology

    1.2.1 Natural systems solve engineering problems.

    From the earliest times we have looked to biological systems for engineering solutions to our technical problems. For example, in Greek mythology the legendary Daedalus, builder of the Cretan labyrinth, was motivated by birds to build wings to help him and his son, Icarus, escape imprisonment. Later observations of birds, such as wing-shape, have led to modern aircraft design features.

    Velcro has been inspired by the way burrs attach themselves to clothing. Autonomous robots can benefit from the study of natural control mechanisms found in similar creatures in the animal kingdom. Machine vision systems for robotics require the separation of objects from the background, a task inherently embedded into the design of natural vision systems. The image recognition capability of humans is difficult to duplicate with computer technology, although neurons are five or six orders of magnitude slower than silicon transistors and heterogeneous (or considerably ‘mismatched’ when compared to transistors).

    1.2.2 Biological information is becoming increasingly more available

    The difficulty in reverse-engineering natural systems is due in part to our lack of complete understanding of these complex systems. In organic chemistry and microbiology, we have uncovered much detail of the fundamental physical processes at the neuronal level. We also have considerable understanding of the overall systems behavior from fields such as psychology or psycho-physics. What is difficult to grasp, however, is how the microscopic processes transforms sensory information into the macroscopic decisions and behaviors. This leads to an interest in natural design optimizations and interconnection schemes.

    It is commonly agreed that many people will do almost anything for money but will also freely give it up for their health. This captures our limited existence in time and space while desiring permanence, which leads to our willingness to do whatever we can to maintain or improve our health. As a result, there is and will always be enormous resources (funds, etc.) available for exploring a deeper understanding of biological phenomena. Although guided for medical purposes, system concepts applicable for other uses will eventually unfold. As we move further into the information age with better and better technology, many of the details are already available for exploiting natural sensory design concepts.

    Although there is already an abundance of information available on natural sensory systems and signal processing, it is difficult for engineers to decipher useful information from the biomedical literature. This is due in part to the different motivations: The medical community is interested in diagnosing (organic) system problems and formulating procedures and medications to fix those problems or allow the patient the ability to adequately deal with the problems. The engineer, on the other hand, is more interested in how specific tasks are accomplished from the available sensory signals.

    1.2.3 Abundant technology is affordable and user-friendly

    Due to rapid advances in processing speeds and throughput capabilities many successful applications have now been developed using artificial intelligence, deep learning neural network architectures, and other related technologies. A small sample of tools readily available for students and researchers include:

    - Reconfigurable computing tools such as Quartus (Altera) and Vitis (Xilinx)

    - Circuit simulation tools such as PSPICE (Microsim)

    - Data Acquisition such as LabVIEW (National Instruments)

    - Computational tools such as Matlab (Mathworks)

    - Development platforms such as Raspberry, Arduino, etc.

    - Languages such as Python

    1.2.4 Research agencies continue to support bio-inspiration

    The author draws from former work experience at the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN). To address the high signal processing throughput and short latency of an imager that guides an exo-atmospheric hypervelocity missile, novel concepts were explored that involved biologically-inspired approaches. Funded concepts included an infrared sensor with retina-inspired readout, multi-resolution targeting inspired by foveated vision, and other research projects exploiting various bio-inspired sensory design ideas.

    Some historical efforts (late 1980’s and 1990’s)

    Much of the work at AFRL/MN was leveraged from former research sponsored by the Defense Advanced Research Projects Agency (DARPA) and the Office of Naval Research (ONR). Research funded by ONR and DARPA as well as National Science Foundation (NSF), National Institute of Health (NIH), and others have resulted in books whose individual chapters are written by the various researchers, which can lead to a considerable lack continuity and consistency. Nevertheless, the material in such books is proven to very useful; a few examples include

    - Mead, Carver, Analog VLSI and Neural Systems, Addison-Wesley, 1989.

    - Zornetzer, Steven, Davis, Joel, and Lau, Clifford, editors, An Introduction to Neural and Electronic Networks, Academic Press, 1990.

    - Ayers, J., Davis, J. and Rudolph, A., editors Neurotechnology for Biomimetic Robots, MIT Press, 2002.

    - Bar-Cohen, Yoseph, and Breazeal, Cynthia, editors, Biologically-inspired Intelligent Robots, Taylor and Francis, 2003.

    - Bar-Cohen, Yoseph, editor, Biomimetics: Biologically-inspired Technologies, Taylor and Francis, 2006.

    The following book and the 2nd edition have been useful for covering the structure and function biological sensory systems:

    - Smith, C.U.M, Biology of Sensory Systems, John Wiley and Sons, ISBN: 0-471-85461-1, 2000.

    As an example of continued strong and direct support for biomimetics, consider this excerpt from an announcement for Biomimetics for Computer Network Security Workshop (1999):

    "The Office of Naval Research is sponsoring a workshop whose goal will be to identify technologies that are inspired by biological foundation and that, when matured, may contribute to a significant increase in network security capability...This research is aimed at developing a new class of biologically inspired robots that exhibit much greater robustness in performance in unstructured environments than today's robots.... The research involves a close collaboration among robotics and physiology researchers at Stanford, U.C. Berkeley, Harvard and Johns Hopkins Universities... sponsored by the Office of Naval Research under grant N00014-98-1-0669…"

    More recent developments

    In August, 2020, the Office of Naval Research (ONR,, Code 341) continued to solicit contract and grant proposals in the area of “Bio-inspired Autonomous Systems” with the following description:

    The aim of Bio-inspired Autonomous Systems is to extract principles of sensorimotor control, biomechanics and fluid dynamics of underwater propulsion and control in aquatic and amphibious animals that underlie the agility, stealth, efficiency, and sensory adaptations of these animals. The principles that emerge from this interdisciplinary research are formalized and explored in advanced prototypes. The goal of this program is to expand the operational envelope of Navy underwater and amphibious vehicles and enable enhanced underwater manipulation.

    as well as in “Bio-inspired Signature Management” with the following description:

    The Bio-inspired Signature Management program aims to discover biologically-inspired adaptations and bioengineered solutions to expand current warfighter capabilities in detection mitigation and undersea navigational challenges. This will be accomplished through multidisciplinary research in science and technology fields such as bio-inspired / biomimetic materials, visual and sensory perception, and bio-optics / bioelectronics.

    Also in August 2020 the Defense Advanced Research Projects Agency (DARPA, gives the following description of their “Nature As Computer (NAC)” program:

    Certain natural processes perform par excellence computation with levels of efficiency unmatched by classical digital models. Levinthal’s Paradox illustrates this well: In nature, proteins fold spontaneously at short timescales (milliseconds) whereas no efficient solution exists for solving protein-folding problems using digital computing. The Nature as Computer (NAC) program proposes that in nature there is synergy between dynamics and physical constraints to accomplish effective computation with minimal resources. NAC aims to develop innovative research concepts that exploit the interplay between dynamic behaviors and intrinsic material properties to develop powerful new forms of computation. The ability to harness physical processes for purposeful computation has already been demonstrated at lab-scales. NAC seeks to apply these concepts to computation challenges that, for fundamental reasons, are poorly suited to, or functionally unexplored with, classical models. NAC will lay the foundation for advancing new theories, design concepts and tools for novel computing substrates, and develop metrics for comparing performance and utility. If successful, NAC will demonstrate the feasibility of solving challenging computation problems with orders-of-magnitude improvements over the state of the art.

    1.2.5 Imitating biology can lead to a better understanding of biology

    Although engineering applications may result from biological inspiration, sometimes those applications are biomedical. For example, artificial neural networks are used for identifying potential cancerous sites in x-ray images. Meanwhile, biomimetic robots are not only used as testbeds for potential engineering applications, but also as tools for biologists to better understand complex animal-environment relationships. An example of this expressed is found concerning MIT’s “RoboLobster” in the following quote:

    The major result of these studies was a solid demonstration that tropotactic concentration-sensing algorithms could not explain the plume-tracking behavior in lobsters…So we are forced to consider other biologically feasible algorithms to find a reasonable explanation…Thus RoboLobster revealed to us something about the lobster’s world that we had previously only suspected: the need to switch tracking strategies between different regions of the plume [Grass02]

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