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Gianluca Rizzello

4 accepted papers

2025

Bi-Modal Self-Sensing Proprioception and Contact Detection in Dielectric Elastomer Soft Robots

RA-L 2025

The development of accurate sensing strategies for soft robotic systems represents an ongoing challenge. In general, it is difficult to integrate a sensory system that preserves the robot's compliance while simultaneously providing accurate measurements. Dielectric elastomer (DE) transducers offer a

Cited by 0SourceScholar
2021

A Hybrid Dynamical Modeling Framework for Shape Memory Alloy Wire Actuated Structures

RA-L 2021

In this letter, a hybrid model for single-crystal Shape Memory Alloy (SMA) wire actuators is presented. The result is based on a mathematical reformulation of the Müller-Achenbach-Seelecke (MAS) model, which provides an accurate and interconnection-oriented description of the SMA hysteretic response

Cited by 7SourceScholar
2021

Smith-Predictor-Based Torque Control of a Rolling Diaphragm Hydrostatic Transmission

RA-L 2021

Rolling Diaphragm Hydrostatic Transmissions (RDHT) are high-performance low-cost solutions to delocalize heavy actuators away from the joints of robotic systems. Exploiting a low-cost pressure-based sensing technique, we propose here a Smith-predictor-based joint torque control of an RDHT-based actu

Cited by 9SourceScholar
2018

Simultaneous Self-Sensing of Displacement and Force for Soft Dielectric Elastomer Actuators

RA-L 2018

This paper presents a novel self-sensing method for soft actuators based on dielectric elastomer (DE) membranes. The proposed self-sensing scheme permits the reconstruction of both membrane force and displacement during actuation, based on voltage and current measurements only. The simultaneous self

Cited by 30SourceScholar