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Tesi etd-06242020-172016


Thesis type
Tesi di dottorato di ricerca
Author
AVERTA, GIUSEPPE BRUNO
URN
etd-06242020-172016
Title
Human-aware Robotics: Modeling Human Motor Skills For The Design, Planning And Control Of A New Generation Of Robotic Devices
Settore scientifico disciplinare
ING-INF/04
Corso di studi
INGEGNERIA DELL'INFORMAZIONE
Supervisors
tutor Prof. Bicchi, Antonio
relatore Prof. Bianchi, Matteo
Parole chiave
  • Control
  • Planning
  • Synergies
  • Rehabilitation
  • Robotics
  • Human-Robot Interaction
  • Neuroscience
Data inizio appello
02/07/2020;
Consultabilità
Parziale
Data di rilascio
02/07/2023
Riassunto analitico
NOTWITHSTANDING the recent advancements of robotics research, nature still highly outperform robots in terms of performances and effectiveness. For this reason, observing the marvelous complexity of human biomechanical structure and the – at least apparent – simplicity in its control, can be of great value to drive significative improvements in robotics technologies. This new field of research crosses the boundaries of several classical disciplines, such as Neuroscience, Psychophysics, Mechatronics, Control Theory. This thesis proposes a trans-disciplinary approach to bridge the gap between the artificial and the natural, by reporting results on the mathematical modeling of human dynamic and kinematic behaviour, with the ultimate goal of providing useful insights for robotic technologies, planning and control as well as for rehabilitation. The central idea of this work is to develop and test mathematical descriptors of human motor control and unveil the main patters that can be used to simplify its codification. To prove the effectiveness of this approach, results are presented – without any loss of generality – focusing on hand and upper limb, with implications for other kinematic structures, such as lower limbs. Innovative planning and control strategies are, then, proposed leveraging on the patterns previously identified. Results show significant improvements in terms of implementation effectiveness and efficiency, thus confirming that a bio-aware development of mechatronic devices could be the key for future advancements of robots, human-machine interaction strategies, rehabilitation and assistive technologies.
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