Control of Biohybrid Actuators Using Neuroevolution

Hugo Alcaraz-Herrera, Michail-Antisthenis Tsompanas, Igor Balaz, Andrew Adamatzky

2024

Abstract

In medical-related tasks, soft robots can perform better than conventional robots because of their compliant building materials and the movements they are able perform. However, designing soft robot controllers is not an easy task, due to the non-linear properties of their materials. A formal design process is needed since human expertise to design such controllers is not sufficiently effective. The present research proposes neuroevolution-based algorithms as the core mechanism to automatically generate controllers for biohybrid actuators that can be used on future medical devices, such as a catheter that will deliver drugs. The controllers generated by methodologies based on Neuroevolution of Augmenting Topologies (NEAT) and Hypercube-based NEAT (HyperNEAT) are compared against the ones generated by a standard genetic algorithm (SGA). In specific, the metrics considered are the maximum displacement in upward bending movement and the robustness to control different biohybrid actuator morphologies without redesigning the control strategy. Results indicate that the neuroevolution-based algorithms produce better-suited controllers than the SGA. In particular, NEAT designed the best controllers, achieving up to 25% higher displacement when compared with SGA-produced specialised controllers trained over a single morphology and 23% when compared with general-purpose controllers trained over a set of morphologies.

Paper Citation

in Harvard Style

Alcaraz-Herrera H., Tsompanas M., Balaz I. and Adamatzky A. (2024). Control of Biohybrid Actuators Using Neuroevolution. In Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: ECTA; ISBN 978-989-758-721-4, SciTePress, pages 197-204. DOI: 10.5220/0012919300003837

in Bibtex Style

@conference{ecta24,
author={Hugo Alcaraz-Herrera and Michail-Antisthenis Tsompanas and Igor Balaz and Andrew Adamatzky},
title={Control of Biohybrid Actuators Using Neuroevolution},
booktitle={Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: ECTA},
year={2024},
pages={197-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012919300003837},
isbn={978-989-758-721-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: ECTA
TI - Control of Biohybrid Actuators Using Neuroevolution
SN - 978-989-758-721-4
AU - Alcaraz-Herrera H.
AU - Tsompanas M.
AU - Balaz I.
AU - Adamatzky A.
PY - 2024
SP - 197
EP - 204
DO - 10.5220/0012919300003837
PB - SciTePress