The research field of evolutionary robotics abstracts some of the major themes in biological evolution (heritable traits, genetic variation, and competition for scarce resources) as tools to allow computers to generate new and interesting virtual creatures. One of the recent themes in this field is towards more embodied robots (those that produce interesting behavior through the design of their bodies, as well as their brains). Here, we build on previous work evolving soft robots to demonstrate the low level embodiment of electrical signals passing information through muscle tissue. Through this work we attempt bridge the divide between embodied cognition and abstracted artificial neural networks. We hope you find the video interesting and entertaining!
This video accompanies the following paper:
Cheney, N., Clune, J., Lipson, H. (2014) “Evolved Electrophysiological Soft Robots”. Proceedings of Artifical Life 14: The Fourteenth International Conference on the Simulation and Synthesis of Living Systems (ALife14). MIT Press.
2013 Soft Robots:
citation: Cheney, N. MacCurdy, R., Clune, J., Lipson, H. (2013) “Unshackling Evolution: Evolving Soft Robots with Multiple Materials and a Powerful Generative Encoding”. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2013). pp. 167-174. ACM.
The work was performed by members of the Cornell Creative Machines Lab (http://creativemachines.cornell.edu)
and the Evolving Artificial Intelligence Lab at the University of Wyoming (http://JeffClune.com)
Special thanks to former lab member Jon Hiller, for the open source soft body simulator VoxCad (www.voxcad.com).
This work was supported by DARPA Open Manufacturing Grant W911NF-12-1-0449 and NASA Space Technology Research Fellowship NNX13AL37H for Nicholas Cheney.
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