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Book Sections Year : 2017

Rapid Prototyping for Bio–Inspired Robots


In this chapter, we explain how embodied AI and enactive cognitive science have enriched robotics with principles, generally specified in so-called bio-inspired robotics. These principles apply on each component of a robotic system (sensors, actuators and controllers) and also on more abstract properties like autonomy, emergence and ecological design. This view has been exemplified with a variety of recently developed systems, particularly considering sensory processing and controller design. Even if these examples report interesting results and propose future avenues of research, the domain of bio-inspired robotics is far from an established and stable domain and many questions remain open to endow it with well-mastered technologies. Particularly, it is clear that the most satisfactory and faithful bio-inspired robots are inspired from primitive animals (e.g: insects) and a long road remains to be done toward a full spectrum of human capabilities. This is clearly linked to the corresponding lack of knowledge in cognitive science where ambitious research program should be launched, particularly concerning what is called Artificial General Intelligence. Having mentioned the need for more accurate information from the biological and cognitive sides, we finally evoke another relevant topic of debate here. For the moment, we have mainly discussed about principles and techniques to design efficient artificial systems, but it is also more and more acknowledged that bio-inspired robotics is also a very good methodology to better understand cognition and its biological foundations. This is undoubtedly another excellent reason to promote research in this domain!
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hal-01427958 , version 1 (06-01-2017)


  • HAL Id : hal-01427958 , version 1


Maria-Jose U Escobar, Frédéric Alexandre, Thierry Viéville, Adrian Palacios. Rapid Prototyping for Bio–Inspired Robots. Rapid Roboting: Recent Advances on 3D Printers and Robotics , Springer, pp.300, 2017, Intelligent Systems, Control and Automation: Science and Engineering. ⟨hal-01427958⟩
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