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Low-power radar-based system for materials and objects recognition

Alessio Sanna

Low-power radar-based system for materials and objects recognition.

Rel. Guido Masera. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering), 2024

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Abstract:

Conventional prosthetic technology for upper limb amputations still suffers from major limitations. Semi-autonomous (i.e., self-grasping) prosthetic hands have been proposed as a promising solution to mitigate some of those limitations. In an effort to contribute to the development of semi-autonomous prosthetic hands, this work explores radars and artificial intelligence algorithms for object recognition. In particular, Pulse-coherent radars and Deep Learning are explored here as potential approaches for in-hand object recognition. The Integration of three radars was undertaken, with a specific emphasis on sensors' timing synchronization to prevent interferences. Subsequently, a detailed data collection and analysis was conducted to recognize the selected items. Finally, offline and real-time investigation into the recognition performance was carried out showing promising results. These findings could be of value for the integration of such low-power, low-cost sensors into prosthetic hands for embedded, real-time object recognition and subsequent autonomous grasping facilitating daily use for individuals with upper limb loss.

Relatori: Guido Masera
Anno accademico: 2023/24
Tipo di pubblicazione: Elettronica
Numero di pagine: 76
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-29 - INGEGNERIA ELETTRONICA
Aziende collaboratrici: Scuola Superiore Sant'Anna
URI: http://webthesis.biblio.polito.it/id/eprint/31050
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