Mr. Eugenio Monari Profile

Eugenio Monari

at Univ. degli Studi di Bologna

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Proceedings Article | 20 April 2022 Presentation + Paper

Multidirectional hemispherical dielectric elastomer proximity sensor for collision avoidance in human-robot interaction applications

Lorenzo Agostini, Eugenio Monari, Marco Caselli, Marco Fontana, Rocco Vertechy

Proceedings Volume 12042, 1204202 (2022) https://doi.org/10.1117/12.2612864

KEYWORDS: Sensors, Electrodes, Robots, Manufacturing, Capacitance, Silicon, Dielectrics, Collision avoidance, Shape analysis, Safety

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Nowadays, several industrial manufacturing processes imply direct cooperation between human operators and robots. This increases production and quality while improving the working conditions. However, the possible presence of physical contact between humans and robots asks for the study and introduction of new technical solutions that aim at guaranteeing a safe Human-Robot Interaction (HRI). Specifically, in recent years, different sensing devices have been developed for collision avoidance monitoring in HRI applications. Generally, common solutions consist of distributed resistive or capacitive sensors networks connected to a central electronic reading board, resulting in a cumbersome layout covering the whole parts of the collaborative robots. In this context, this paper presents an innovative tactile and proximity sensing strategy based on a soft-sensor module that can be installed on the collaborative robot parts or surrounding workspace. The developed module consists of a capacitive sensor based on a silicone elastomer membrane with compliant electrodes attached to the surface, disposed homogeneously on a deformable hemisphere-shape made of silicone. Thanks to the geometrical layout, such a sensor allows multidirectional objects detection resulting in a promising non-invasive solution for collisions avoidance in HRI applications. This work reports the design, manufacturing, and preliminary experimental investigation of such a sensor module, evaluating the electrodes geometry and the most relevant features that optimize objects detection distance and directivity sensing performance.

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