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2021 | OriginalPaper | Chapter

Regenerating Soft Robots Through Neural Cellular Automata

Authors : Kazuya Horibe, Kathryn Walker, Sebastian Risi

Published in: Genetic Programming

Publisher: Springer International Publishing

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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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Title: Regenerating Soft Robots Through Neural Cellular Automata
Authors: Kazuya Horibe
Kathryn Walker
Sebastian Risi
Publisher: Springer International Publishing
Book: Genetic Programming
Print ISBN: 978-3-030-72811-3

Electronic ISBN: 978-3-030-72812-0

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-72812-0_3

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