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Frontiers in Tactile Sensors
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Frontiers in Tactile Sensors

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 11411

Special Issue Editor

Dr. Meng-Fang Lin

E-Mail Website
Guest Editor
Department of Materials Engineering, Ming Chi University of Technology, New Taipei City 24301, Taiwan
Interests: nanomaterial; composite; flexible electronics; energy harvesting; actuator; tactile sensor; human–machine interfaces
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Tremendous advances in the development of tactile sensors have led to their use in a wide range of practical applications including electronic devices such as touchscreens for mobile phones and computers. In an abstract way, these sensors mimic the human sense of touch by converting some quantity associated with physical touch into processable information. In practice, “physical touch” can be represented by measurable properties such as temperature, vibration, softness, texture, shape, composition shear as well as normal force or combinations thereof. This Special Issue, “Frontiers in Tactile Sensors”, is dedicated to gathering research articles, short communications and review articles on recent developments in the field of tactile sensors as a focussed source of information intended to inspire future innovations in the field.

Acceptable topics may include—but are by no means limited to—flexible electronics, healthcare applications, disease diagnosis, biomedical materials, opportunities and challenges of concurrent tactile sensors, and other sensor applications. We invite researchers in this field to submit relevant manuscripts to this Special Issue of the journal Sensors.

Prof. Dr. Meng-Fang Lin
Guest Editor

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 submissions that pass pre-check are 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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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

  • sensor
  • thin film
  • flexible electronics
  • healthcare
  • disease diagnosis
  • wearable device
  • application
  • automation
  • biomedicine
  • robotics

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Published Papers (3 papers)

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Research

17 pages, 13681 KiB  
Article
Effects of Sensing Tactile Arrays, Shear Force, and Proprioception of Robot on Texture Recognition
by Jung-Hwan Yang, Seong-Yong Kim and Soo-Chul Lim
Sensors 2023, 23(6), 3201; https://doi.org/10.3390/s23063201 - 17 Mar 2023
Cited by 9 | Viewed by 3683
Abstract
In robotics, tactile perception is important for fine control using robot grippers and hands. To effectively incorporate tactile perception in robots, it is essential to understand how humans use mechanoreceptors and proprioceptors to perceive texture. Thus, our study aimed to investigate the impact [...] Read more.
In robotics, tactile perception is important for fine control using robot grippers and hands. To effectively incorporate tactile perception in robots, it is essential to understand how humans use mechanoreceptors and proprioceptors to perceive texture. Thus, our study aimed to investigate the impact of tactile sensor arrays, shear force, and the positional information of the robot’s end effector on its ability to recognize texture. A deep learning network was employed to classify tactile data from 24 different textures that were explored by a robot. The input values of the deep learning network were modified based on variations in the number of channels of the tactile signal, the arrangement of the tactile sensor, the presence or absence of shear force, and the positional information of the robot. By comparing the accuracy of texture recognition, our analysis revealed that tactile sensor arrays more accurately recognized the texture compared to a single tactile sensor. The utilization of shear force and positional information of the robot resulted in an improved accuracy of texture recognition when using a single tactile sensor. Furthermore, an equal number of sensors placed in a vertical arrangement led to a more accurate distinction of textures during exploration when compared to sensors placed in a horizontal arrangement. The results of this study indicate that the implementation of a tactile sensor array should be prioritized over a single sensor for enhanced accuracy in tactile sensing, and the use of integrated data should be considered for single tactile sensing. Full article
(This article belongs to the Special Issue Frontiers in Tactile Sensors)
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11 pages, 2741 KiB  
Article
Cesium Lead Bromide Nanocrystals: Synthesis, Modification, and Application to O2 Sensing
by Zhi-Hao Huang, Madhuja Layek, Chia-Feng Li, Kun-Mu Lee and Yu-Ching Huang
Sensors 2022, 22(22), 8853; https://doi.org/10.3390/s22228853 - 16 Nov 2022
Cited by 2 | Viewed by 2299
Abstract
The fluorescence intensity of inorganic CsPbBr3 (CPB) perovskite nanocrystals (NCs) decreases in the presence of O2. In this study, we synthesized CPB NCs with various shapes and sizes for use as optical gas sensing materials. We fabricated O2 gas [...] Read more.
The fluorescence intensity of inorganic CsPbBr3 (CPB) perovskite nanocrystals (NCs) decreases in the presence of O2. In this study, we synthesized CPB NCs with various shapes and sizes for use as optical gas sensing materials. We fabricated O2 gas sensors from the various CPB NCs on several porous and nonporous substrates and examined the effects of the NC shapes and aggregate sizes and the substrate pore size on the device response. Our sensor fabricated from CPB nanocrystals on a porous substrate exhibited the highest response; the porous substrate allowed the rapid diffusion of O2 such that the NC surface was exposed effectively to the gas. Thus, the interfacial interaction between NC surfaces and substrates is a critical factor for consideration when preparing gas sensors with a high response. Full article
(This article belongs to the Special Issue Frontiers in Tactile Sensors)
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22 pages, 20814 KiB  
Article
HiVTac: A High-Speed Vision-Based Tactile Sensor for Precise and Real-Time Force Reconstruction with Fewer Markers
by Shengjiang Quan, Xiao Liang, Hairui Zhu, Masahiro Hirano and Yuji Yamakawa
Sensors 2022, 22(11), 4196; https://doi.org/10.3390/s22114196 - 31 May 2022
Cited by 10 | Viewed by 4123
Abstract
Although they have been under development for years and are attracting a lot of attention, vision-based tactile sensors still have common defects—the use of such devices to infer the direction of external forces is poorly investigated, and the operating frequency is too low [...] Read more.
Although they have been under development for years and are attracting a lot of attention, vision-based tactile sensors still have common defects—the use of such devices to infer the direction of external forces is poorly investigated, and the operating frequency is too low for them to be applied in practical scenarios. Moreover, discussion of the deformation of elastomers used in vision-based tactile sensors remains insufficient. This research focuses on analyzing the deformation of a thin elastic layer on a vision-based tactile sensor by establishing a simplified deformation model, which is cross-validated using the finite element method. Further, this model suggests a reduction in the number of markers required by a vision-based tactile sensor. In subsequent testing, a prototype HiVTac is fabricated, and it demonstrates superior accuracy to its vision-based tactile sensor counterparts in reconstructing an external force. The average error of inferring the direction of external force is 0.32∘, and the root mean squared error of inferring the magnitude of the external force is 0.0098 N. The prototype was capable of working at a sampling rate of 100 Hz and a processing frequency of 1.3 kHz, even on a general PC, allowing for real-time reconstructions of not only the direction but also the magnitude of an external force. Full article
(This article belongs to the Special Issue Frontiers in Tactile Sensors)
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