Iterative learning control as a framework for human-inspired control with bio-mimetic actuators
| Autor: | Angelini, Franco, Bianchi, Matteo, Garabini, Manolo, Bicchi, Antonio, Della Santina, C., Vouloutsi, Vasiliki, Mura, Anna, Verschure, Paul F. M. J., Tauber, Falk, Speck, Thomas, Prescott, Tony J. |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Motion and motor control Exploit Human-inspired control Computer science Iterative learning control Control engineering 02 engineering and technology 03 medical and health sciences 020901 industrial engineering & automation 0302 clinical medicine Robotic systems Control point Robot Actuator Control (linguistics) Robotic arm 030217 neurology & neurosurgery Natural machine motion |
| Zdroj: | Biomimetic and Biohybrid Systems-9th International Conference, Living Machines 2020, Freiburg, Germany, July 28–30, 2020, Proceedings Biomimetic and Biohybrid Systems: Proceedings of the 9th International Conference, Living Machines 2020 Biomimetic and Biohybrid Systems Lecture Notes in Computer Science Lecture Notes in Computer Science-Biomimetic and Biohybrid Systems Biomimetic and Biohybrid Systems ISBN: 9783030643126 Living Machines |
| ISSN: | 0302-9743 1611-3349 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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