The synergy between musculoskeletal and central nervous systems empowers humans to achieve a high level of motor performance, which is still unmatched in bio-inspired robotic systems. Literature already presents a wide range of robots that mimic the human body. However, under a control point of view, substantial advancements are still needed to fully exploit the new possibilities provided by these systems. In this paper, we test experimentally that an Iterative Learning Control algorithm can be used to reproduce functionalities of the human central nervous system - i.e. learning by repetition, after-effect on known trajectories and anticipatory behavior - while controlling a bio-mimetically actuated robotic arm.
|Title of host publication||Biomimetic and Biohybrid Systems|
|Subtitle of host publication||Proceedings of the 9th International Conference, Living Machines 2020|
|Editors||Vasiliki Vouloutsi, Anna Mura, Paul F. M. J. Verschure, Falk Tauber, Thomas Speck, Tony J. Prescott|
|Publication status||Published - 2021|
|Event||9th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2020 - Virtual, Online|
Duration: 28 Jul 2019 → 30 Jul 2019
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||9th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2020|
|Period||28/07/19 → 30/07/19|
Bibliographical noteGreen Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise 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.
- Human-inspired control
- Motion and motor control
- Natural machine motion