
Mohamad Jawad Naim
Multimodal Haptic Feedback in a Soft Robotic Ball for Therapeutic Human–Robot Interaction (MR2S).
Rel. Pangcheng David Cen Cheng. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2025
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Abstract: |
As part of the MR2S project, this research explores the development of robotic systems intended for therapeutic interaction in healthcare, with a particular focus on autism support. In such contexts, soft and responsive haptic devices offer a compelling non-verbal channel to promote emotional engagement and sensory regulation. The thesis presents the development of a tactile interaction system that responds to varying levels of physical input using capacitive sensing and multimodal feedback. The goal was to create a clear and compact platform capable of detecting graded touch and translating it into both vibration and mechanical motion responses. The sensing was handled by a soft resistive-capacitive material, able to reflect different pressure levels through measurable resistance changes. Five interaction categories were defined (no touch, soft touch, medium touch, hard touch, grab touch) and each was mapped to a corresponding response in vibration motors and servo-based motion. The Arduino Mega 2560 was selected as the most suitable controller because of its wide pin availability and steady analog input handling. Each function of the system including sensor reading, classification, vibration triggering, and servo actuation was first developed and tested independently, before being brought into a unified loop. The logic used was deliberately simple, relying on threshold comparisons and step-wise control to maintain transparency and responsiveness. Python scripts were used to visualize sensor behavior, refine thresholds, and validate the classification process with greater flexibility than the standard Arduino tools. The resulting implementation showed reliable, repeatable feedback patterns across all defined interaction levels. The system’s structure allows for easy adaptation, and its components work together to illustrate how simple, soft sensors can drive multimodal feedback in real time. This platform may support future applications in wearable feedback, soft robotics, or therapeutic devices requiring low-latency tactile response. |
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Relatori: | Pangcheng David Cen Cheng |
Anno accademico: | 2024/25 |
Tipo di pubblicazione: | Elettronica |
Numero di pagine: | 82 |
Soggetti: | |
Corso di laurea: | Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica) |
Classe di laurea: | Nuovo ordinamento > Laurea magistrale > LM-25 - INGEGNERIA DELL'AUTOMAZIONE |
Ente in cotutela: | École Nat. Sup. de l'Électronique et de ses Applications (ENSEA) (FRANCIA) |
Aziende collaboratrici: | École Nationale Supérieure de l'Électronique et de ses Applications (ENSEA) |
URI: | http://webthesis.biblio.polito.it/id/eprint/36537 |
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