ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-11182021-113222


Tipo di tesi
Tesi di laurea magistrale
Autore
CAMPINOTI, GIULIA
URN
etd-11182021-113222
Titolo
Soft arm proprioception system based on soft strain sensors
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
BIONICS ENGINEERING
Relatori
relatore Prof. Cianchetti, Matteo
correlatore Dott.ssa Maselli, Martina
Parole chiave
  • soft sensors
  • I-Support
  • proprioception
  • soft robotics
Data inizio appello
03/12/2021
Consultabilità
Non consultabile
Data di rilascio
03/12/2024
Riassunto
Soft robots are devices that actively interact with the environment and have distributed large deformations due to their inherent structural compliance. These characteristics make them preferable with respect to traditional robotic solutions in a variety of fields, such as wearable robotics, medical and surgical applications and assistive robotics. A limit in the diffusion of soft robots is the difficulty in embedding a sensory system that does not limit the movements of the robot and that allows a good estimation of the end-effector position. Aim of this work is to investigate solutions for this problem, in particular with respect to the I-Support module, a soft robotic arm meant to help the elderly in performing the task of showering. In this work, after a preliminary analysis of available soft sensing techniques, commercial piezoresistive textile Electrolycra was chosen to be a good candidate for the application as a strain sensor. After an electromechanical characterization, sensors made of Electrolycra were applied to the I-Support module. Relying on a derived calibration curve and on the constant curvature approximation, performances in terms of position tracking have been found. The sensing system and the estimation method is proved to able to track the position of the end-effector with an error of respectively 13.1 mm, 13.7 mm and 4.8 mm in the x,y and z coordinate of a global reference frame when the robot is actuated to explore its workspace. These results are encouraging and can pave the way for further uses in terms of closed loop control.
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