Abstract
The compliant nature of soft robots is appealing to a wide range of applications. However, this compliant property also poses several control challenges, e.g., how to deal with infinite degrees of freedom and highly nonlinear behaviors. This paper proposes a hybrid controller for a pneumatic-actuated soft robot. To this end, a model-based feedforward controller is designed and combined with a correction torque calculated via Gaussian process regression. Then, the proposed model-based and hybrid controllers are experimentally validated, and a detailed comparison between controllers is presented. Notably, the experimental results highlight the potential benefits of adding a learning approach to a model-based controller to enhance the closed-loop performance while reducing the computational load exhibited by purely learning strategies.
Original language | English |
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Title of host publication | Human-Friendly Robotics 2023 - HFR |
Subtitle of host publication | 16th International Workshop on Human-Friendly Robotics |
Editors | Cristina Piazza, Patricia Capsi-Morales, Luis Figueredo, Manuel Keppler, Hinrich Schütze |
Publisher | Springer |
Pages | 19-35 |
Number of pages | 17 |
ISBN (Print) | 978-3-031-54999-1 |
DOIs | |
Publication status | Published - 2024 |
Event | 16th International Workshop on Human-Friendly Robotics, HFR 2023 - Munich, Germany Duration: 20 Sept 2023 → 21 Sept 2023 |
Publication series
Name | Springer Proceedings in Advanced Robotics |
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Volume | 29 SPAR |
ISSN (Print) | 2511-1256 |
ISSN (Electronic) | 2511-1264 |
Conference
Conference | 16th International Workshop on Human-Friendly Robotics, HFR 2023 |
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Country/Territory | Germany |
City | Munich |
Period | 20/09/23 → 21/09/23 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.