BioInspired! So What? Now What!

We often describe biom* as the process of transferring or translating knowledge from biology into the technology domain.  Both the problem-driven and solution-driven pathways assume knowledge of the biological phenomenon exists in a form that can be efficiently transferred and applied to solve meaningful technical problems in a reliable/scalable manner.  Anecdotal evidence suggests that these assumptions may hold true in a small set of circumstances but break down in more complicated situations, sometimes resulting in shallow forms of biom* driven more by metaphor than a deeper understanding of nature.

There appears to be a third pathway involving expertise that straddles the domains of biology and technology.  In ZQ16, Peter Niewiarowski talked about "creat[ing] a 'space' that encompasses the important knowledge fields and ideally enhances all of them".  Some examples:

• Rolf Mueller (physicist):  understanding the morphology and function of bat ears and the implications for range of technical challenges
• John Dabiri (aerodynamics): understanding the fluid dynamics of fish schooling and the application to wind turbine positioning
• Annick Bay (photonics) : understanding the anatomy of the firefly's anatomy and how the knowledge could increase LED efficiency

Building Robots That Can Go Where We Go (Jonathan Hurst) is an example of applying the latest engineering research methods to understand legged locomotion, develop mathematical models, and test the models by building bipedal robots.  Hurst's team also developed metrics (ability, power consumption, force levels) that assess the gap between our implementations and the natural analogues, creating a feedback loop between research and implementation.  This type of 'action research' can reduce timelines and increase credibility in the early stages.

'Knowledge mobilisation' encourages us to invest in expanding and integrating knowledge across domains and explore opportunities for transdisciplinary collaboration to deal with more complex problems.  If you are aware of other examples, please let me know.

Amoeboid Robot Navigates Without a Brain shows the value of 'closing the loop':

• investigating a natural phenomenon in depth, rather than relying on surface impressions
• abstracting the underlying principles, rather than superficial similarities
• making the principles tangible so that they can be tested
• and lastly comparing the outcome with the original inspiration to further deepen our understanding