Model-based control can improve the performance of artificial cilia

Edoardo Milana, Francesco Stella, Benjamin Gorissen, Dominiek Reynaerts, Cosimo Della Santina

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Artificial cilia are a prominent example of physical intelligence. Their mechanical properties are often designed so to achieve desired motions in response to very simple actuation patterns. Yet, variability in the mechanical properties are inherent in these systems. This may critically disrupt the input-output relation, resulting in a final behavior completely different from the desired one. In this Communication we investigate the possibility of designing a robotic brain that helps the cilium to maintain its physical intelligence. We achieve that by closing a model-based control loop which tracks the position of the end effector while compensating for drag forces. We propose experiments to characterize our model, and extensive simulations validating the results in different conditions. This work is intended as a proof of concept, which will be further expanded in future work.

Original languageEnglish
Title of host publication2021 IEEE 4th International Conference on Soft Robotics, RoboSoft 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages527-530
Number of pages4
ISBN (Electronic)9781728177137
DOIs
StatePublished - 12 Apr 2021
Externally publishedYes
Event4th IEEE International Conference on Soft Robotics, RoboSoft 2021 - New Haven, United States
Duration: 12 Apr 202116 Apr 2021

Publication series

Name2021 IEEE 4th International Conference on Soft Robotics, RoboSoft 2021

Conference

Conference4th IEEE International Conference on Soft Robotics, RoboSoft 2021
Country/TerritoryUnited States
CityNew Haven
Period12/04/2116/04/21

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