Special Issue "Tactile Sensing for Soft Robotics and Wearables"

A special issue of Micromachines (ISSN 2072-666X).

Deadline for manuscript submissions: closed (30 April 2018)

Special Issue Editors

Guest Editor
Dr. Lucia Beccai

Center for Micro-Biorobotics, Istituto Italiano di Tecnologia (IIT), Pontedera (Pisa), Italy
Website1 | Website2 | E-Mail
Phone: +39-050-883-079(400)
Interests: artificial touch; mechanotransduction; biorobotics; soft robotics; 3D lithography; mechanical sensing; soft MEMS/NEMS
Guest Editor
Dr. Massimo Totaro

Center for Micro-Biorobotics, Istituto Italiano di Tecnologia (IIT), Pontedera (Pisa), Italy
Website | E-Mail
Phone: +39-050-883-015
Interests: tactile sensing; nanotechnology; soft robotics; MEMS/NEMS; FEM electromechanical modeling

Special Issue Information

Dear Colleagues,

In recent years, rapid developments in tactile sensing have mainly been due to the advent of novel deformable materials, mimicking skin flexibility and elasticity. In addition to single sensors, electronic skins built from both inorganic and organic electronic materials have boosted up, especially ultra-thin and ultra-conformable systems. However, many aspects require new concepts at component, as well as at system, levels. For example, effective solutions for achieving multimodality are needed. Indeed, information of various types (e.g., pressure, temperature, humidity, etc.) should be detected in a robust and reliable manner, and in large area issues of real-time signal processing are posed, as well of wiring and connections. Additionally, today, new challenges emerge from soft robotic approaches and wearable systems, where the use of deformable sensors becomes crucial for encoding a variety of information that are not only provided by the external world, but also by the deformation of the hosting robot/human body. This Special Issue seeks to showcase research papers, short communications, and review articles on novel developments of soft tactile sensing, and mechanical sensing more at large. The focus is on new designs and models, new materials and fabrication processes, advanced signal processing and innovative machine learning algorithms that could be useful to target real applications in both in robotics and wearable systems, e.g., biomimetic skins, smart surgical tools, wearables for monitoring vital parameters (e.g., body temperature, blood pulse) and body movements.

Dr. Lucia Beccai
Dr. Massimo Totaro
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Artificial touch
  • Soft robotics
  • Mechanical sensors
  • Wearable systems
  • Soft materials
  • Machine learning

Published Papers (1 paper)

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Research

Open AccessArticle Decoupling Research of a Novel Three-Dimensional Force Flexible Tactile Sensor Based on an Improved BP Algorithm
Micromachines 2018, 9(5), 236; https://doi.org/10.3390/mi9050236
Received: 26 March 2018 / Revised: 10 May 2018 / Accepted: 11 May 2018 / Published: 14 May 2018
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Abstract
Decoupling research on flexible tactile sensors play a very important role in the intelligent robot skin and tactile-sensing fields. In this paper, an efficient machine learning method based on the improved back-propagation (BP) algorithm is proposed to decouple the mapping relationship between the
[...] Read more.
Decoupling research on flexible tactile sensors play a very important role in the intelligent robot skin and tactile-sensing fields. In this paper, an efficient machine learning method based on the improved back-propagation (BP) algorithm is proposed to decouple the mapping relationship between the resistances of force-sensitive conductive pillars and three-dimensional forces for the 6 × 6 novel flexible tactile sensor array. Tactile-sensing principles and numerical experiments are analyzed. The tactile sensor array model accomplishes the decomposition of the force components by its delicate structure, and avoids direct interference among the electrodes of the sensor array. The force components loaded on the tactile sensor are decoupled with a very high precision from the resistance signal by the improved BP algorithm. The decoupling results show that the k-cross validation (k-CV) algorithm is a highly effective method to improve the decoupling precision of force components for the novel tactile sensor. The large dataset with the k-CV method obtains a better decoupling accuracy of the force components than the small dataset. All of the decoupling results are fairly good, and they indicate that the improved BP model with a strong non-linear approaching ability has an efficient and valid performance in decoupling force components for the tactile sensor. Full article
(This article belongs to the Special Issue Tactile Sensing for Soft Robotics and Wearables)
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