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Impact of Morphology Variations on Evolved Neural Controllers for Modular Robots

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Artificial Life and Evolutionary Computation (WIVACE 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1780))

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Abstract

Modular robots, in particular those in which the modules are physically interchangeable, are suitable to be evolved because they allow for many different designs. Moreover, they can constitute ecosystems where “old” robots are disassembled and the resulting modules are composed together, either within an external assembling facility or by self-assembly procedures, to form new robots. However, in practical settings, self-assembly may result in morphologies that are slightly different from the expected ones: this may cause a detrimental misalignment between controller and morphology. Here, we characterize experimentally the robustness of neural controllers for Voxel-based Soft Robots, a kind of modular robots, with respect to small variations in the morphology. We employ evolutionary computation for optimizing the controllers and assess the impact of morphology variations along two axes: kind of morphology and size of the robot. Moreover, we quantify the advantage of performing a re-optimization of the controller for the varied morphology. Our results show that small variations in the morphology are in general detrimental for the performance of the evolved neural controller. Yet, a short re-optimization is often sufficient for aligning back the performance of the modified robot to the original one.

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Author information

Authors and Affiliations

  1. Department of Engineering and Architecture, University of Trieste, Trieste, Italy

    Eric Medvet

  2. Department of Mathematics and Geosciences, University of Trieste, Trieste, Italy

    Francesco Rusin

Authors
  1. Eric Medvet
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  2. Francesco Rusin
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Correspondence to Eric Medvet .

Editor information

Editors and Affiliations

  1. University of Cassino and Southern Lazio, Cassino, Italy

    Claudio De Stefano

  2. University of Cassino and Southern Lazio, Gaeta, Italy

    Francesco Fontanella

  3. Universidade Nova de Lisboa, Lisbon, Portugal

    Leonardo Vanneschi

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Medvet, E., Rusin, F. (2023). Impact of Morphology Variations on Evolved Neural Controllers for Modular Robots. In: De Stefano, C., Fontanella, F., Vanneschi, L. (eds) Artificial Life and Evolutionary Computation. WIVACE 2022. Communications in Computer and Information Science, vol 1780. Springer, Cham. https://doi.org/10.1007/978-3-031-31183-3_22

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  • DOI: https://doi.org/10.1007/978-3-031-31183-3_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-31182-6

  • Online ISBN: 978-3-031-31183-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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