1.3 Academic research activity
Using natural biology as a source of inspiration for solving sensing problems requires a solid understanding of biology. Although there is a long history of our understanding how biological sensory systems perform certain tasks, there is still very much that is not yet understood. Biological research institutions continually reveal deeper knowledge of the structure and function of sensory systems, which gives engineering problem-solvers more to consider. Models and algorithms are developed to match measured data, such as the Hassenstein-Reichardt Elementary Motion Detection (HR-EMD) model [Hass56], DeValois spatial vision models [DeV88], and others more focused on a specific sensory system, such as Frank Werblin’s efforts to simulate primate vision processing in the retina [Werb91], John Douglas’ and Nicholas Strausfeld’s work to map the neural circuitry of the fly [Doug00], and many others.
Sometimes biology is deliberately considered for inspiration for new ideas. One example is the funding provided during the 1980’s by the Office of Naval Research (ONR) and the Defense Advanced Research Project Agency (DARPA) to pursue novel military sensor designs. One of the products is a collection of biologically-inspired sensory system design concepts implemented in VLSI technology. Several of these designs developed at California Institute of Technology (CalTech) are detailed in Analog VLSI and Neural System [Mead89]. One of these designs, the ‘silicon retina’, was expanded by the Air Force Research Laboratory (AFRL) for military seeker applications by integrating with an array of infrared sensors [Mass93]. Some graduates from Mead’s lab began their own bio-inspired labs at institutions such as Georgia Institute of Technology, University of Florida, Massachusetts Institute of Technology, etc. while other graduates started their own companies building bio-inspired components or researching follow-on design concepts.
Much more work in bio-inspired sensing can be found in technical journals and conferences such as the IEEE International Conference on Robotics and Biomimetics. This conference alone has more than 500 papers and has been an annual conference since 2012. A common application for this conference is robotic fish, which has its inspiration in the design of fish for underwater maneuverability. Other popular topics include deep-learning neural networks, actuators, flocking (or swarming), and biomimetic materials. These topics are popular in other bio-inspired conferences, journals magazines, etc. Although the original neural network is bio-inspired, many subsequent efforts deviate from biology (not to mention very little is known about how real neural networks work). Any research using a neural network or adding something to a robotic fish or other originally bio-inspired concept could arguably be labeled ‘bio-inspired’, which complicates isolating truly new bio-inspired contributions.
In addition to the technology applications we have the more biology-focused efforts, where biologists are attempting to derive models that adequately reflect measured data. Example journals include Vision Research and Biological Cybernetics. A drawback for engineers is the biology-intensive language necessary to convey their models, as well as efforts typically are very focused on a very specific part of one species’ neural circuitry, such as the mechanism for turning in the salamander [Liu20]. Therefore due to the quantity of technical efforts and the wide diversity of disciplines that consider this general topic area it is quite challenging to encompass all significant efforts in any of the basic modalities (vision, olfaction, gustation, tactile, audition) of bio-inspired sensory design.