Tesi etd-05062024-162042 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
SUSINI, PAOLO
URN
etd-05062024-162042
Titolo
Compliance discrimination via optical tactile sensors
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA ROBOTICA E DELL'AUTOMAZIONE
Relatori
relatore Prof. Bianchi, Matteo
relatore Prof. Lepora, Nathan F.
correlatore Pagnanelli, Giulia
relatore Prof. Lepora, Nathan F.
correlatore Pagnanelli, Giulia
Parole chiave
- artificial intelligence
- compliance estimation
- deep learning
- haptics
- soft sensor
- tactile sensing
- TacTip
Data inizio appello
06/06/2024
Consultabilità
Non consultabile
Data di rilascio
06/06/2094
Riassunto
In this work has been developed brand new deep learning algorithms to estimate the compliance of objects using a soft tactile sensor designed at the BRL, the TacTip.
The data acquisition and elaboration has been explained and how to make those datas suitable for the purpose of the project.
Online and offline results are showed and commented in order to draw conclusion.
A brief comparison between my data-driven method and a state of the art model-based method is reported.
The data acquisition and elaboration has been explained and how to make those datas suitable for the purpose of the project.
Online and offline results are showed and commented in order to draw conclusion.
A brief comparison between my data-driven method and a state of the art model-based method is reported.
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