Literature DB >> 29251568

Integrated Simultaneous Detection of Tactile and Bending Cues for Soft Robotics.

Massimo Totaro1, Alessio Mondini1, Andrea Bellacicca2, Paolo Milani2, Lucia Beccai1.   

Abstract

Soft robots should move in an unstructured environment and explore it and, to do so, they should be able to measure and distinguish proprioceptive and exteroceptive stimuli. This can be done by embedding mechanosensing systems in the body of the robot. Here, we present a polydimethylsiloxane block sensorized with an electro-optical system and a resistive strain gauge made with the supersonic cluster beam implantation (SCBI) technique. We show how to integrate these sensing elements during the whole fabrication process of the soft body and we demonstrate that their presence does not change the mechanical properties of the bulk material. Exploiting the position of both sensing systems and a proper combination of the output signals, we present a strategy to measure simultaneously external pressure and positive/negative bending of the body. In particular, the optical system can reveal any mechanical stimulation (external from the soft block or due to its own deformation), while the resistive strain gauge is insensitive to the external pressure, but sensitive to the bending of the body. This solution, here applied to a simple block of soft material, could be extended to the whole body of a soft robot. This approach provides detection and discrimination of the two stimuli (pressure and bending), with low computational effort and without significant mechanical constraint.

Entities:  

Keywords:  nanocomposite; soft robotics; stretchable electronics; tactile sensing

Year:  2017        PMID: 29251568     DOI: 10.1089/soro.2016.0049

Source DB:  PubMed          Journal:  Soft Robot        ISSN: 2169-5172            Impact factor:   8.071


  2 in total

1.  Mechanoreception for Soft Robots via Intuitive Body Cues.

Authors:  Liangliang Wang; Zheng Wang
Journal:  Soft Robot       Date:  2019-11-05       Impact factor: 8.071

Review 2.  Toward Perceptive Soft Robots: Progress and Challenges.

Authors:  Hongbo Wang; Massimo Totaro; Lucia Beccai
Journal:  Adv Sci (Weinh)       Date:  2018-07-13       Impact factor: 16.806

  2 in total

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