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Regenerating Soft Robots Through Neural Cellular Automata

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Book cover Genetic Programming (EuroGP 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12691))

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Abstract

Morphological regeneration is an important feature that highlights the environmental adaptive capacity of biological systems. Lack of this regenerative capacity significantly limits the resilience of machines and the environments they can operate in. To aid in addressing this gap, we develop an approach for simulated soft robots to regrow parts of their morphology when being damaged. Although numerical simulations using soft robots have played an important role in their design, evolving soft robots with regenerative capabilities have so far received comparable little attention. Here we propose a model for soft robots that regenerate through a neural cellular automata. Importantly, this approach only relies on local cell information to regrow damaged components, opening interesting possibilities for physical regenerable soft robots in the future. Our approach allows simulated soft robots that are damaged to partially regenerate their original morphology through local cell interactions alone and regain some of their ability to locomote. These results take a step towards equipping artificial systems with regenerative capacities and could potentially allow for more robust operations in a variety of situations and environments. The code for the experiments in this paper is available at: http://github.com/KazuyaHoribe/RegeneratingSoftRobots.

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Acknowledgements

This work was supported by the Tobitate! (Leap for Tomorrow) Young Ambassador Program, a Sapere Aude: DFF-Starting Grant (9063-00046B), and KH’s Academist supporters (https://academist-cf.com/projects/119?lang=en) (Takaaki Aoki, Hirohito M. Kondo, Takeshi Oura, Yusuke Kajimoto, Ryuta Aoki).

Author information

Authors and Affiliations

  1. IT University of Copenhagen, Copenhagen, Denmark

    Kazuya Horibe, Kathryn Walker & Sebastian Risi

  2. Osaka University, Osaka, Japan

    Kazuya Horibe

  3. Cross Labs, Cross Compass Ltd., Tokyo, Japan

    Kazuya Horibe

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  1. Kazuya Horibe
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  2. Kathryn Walker
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  3. Sebastian Risi
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Editors and Affiliations

  1. Queen’s University, Kingston, ON, Canada

    Ting Hu

  2. University of Coimbra, Coimbra, Portugal

    Nuno Lourenço

  3. University of Trieste, Trieste, Italy

    Eric Medvet

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Horibe, K., Walker, K., Risi, S. (2021). Regenerating Soft Robots Through Neural Cellular Automata. In: Hu, T., Lourenço, N., Medvet, E. (eds) Genetic Programming. EuroGP 2021. Lecture Notes in Computer Science(), vol 12691. Springer, Cham. https://doi.org/10.1007/978-3-030-72812-0_3

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  • DOI: https://doi.org/10.1007/978-3-030-72812-0_3

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