Predicting soft robot's locomotion fitness

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Abstract

Organisms with different body morphology and movement dynamics have distinct abilities to move through the environment. Despite such truism, there is a lack of general principles that predict which shapes and dynamics make the organisms more fit to move. Studying a minimal yet embodied soft robot model under the influence of gravity, we find three features that predict robot locomotion fitness: (1) A larger body is better. (2) Two-point contact with the ground is better than one-point contact. (3) Out-of-phase oscillating body parts increase locomotion fitness. These design principles can guide the selection rules for evolutionary algorithms to obtain robots with higher locomotion fitness.

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APA

Biazzi, R. B., Fujita, A., & Takahashi, D. Y. (2021). Predicting soft robot’s locomotion fitness. In GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion (pp. 81–82). Association for Computing Machinery, Inc. https://doi.org/10.1145/3449726.3459417

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