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Tactile Sensors, Sensing and Systems
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Tactile Sensors, Sensing and Systems

A topical collection in Sensors (ISSN 1424-8220). This collection belongs to the section "Physical Sensors".

Viewed by 4247

Editor

Prof. Dr. Maurizio Valle

E-Mail Website
Collection Editor
Department of Electrical, Electronic and Telecommunications Engineering, and Naval Architecture, University of Genova, Via Opera Pia 11A, I16145 Genova, Italy
Interests: biomedical circuits and systems; electronic/artificial sensitive skin; tactile sensing systems for prosthetics and robotics; neuromorphic touch sensors; electronic and microelectronic systems
Special Issues, Collections and Topics in MDPI journals

Topical Collection Information

Dear Colleagues,

Tactile sensing is built upon mechanical sensors distributed over a given surface (e.g. robotic hand/arm, outer cover of an apparatus or a consumer device) on which physical/mechanical contact/interaction may occur. The sensors upon a mechanical interaction perceive the event and acquire data on the contact such as temperature, vibration, pressure, shear and normal forces. Raw sensed data are then processed to extract higher-level information (e.g. surface texture patterns and roughness, softness/hardness, object contact material) which is subsequently conveyed to the control/supervising system. The acquisition and processing operations are usually implemented in real time. Tactile arrays ought to be mechanically flexible (i.e., conformable to the surface they are mounted on) and sometimes stretchable.

Recent and relevant achievements in materials and transducers have not yet successfully boosted system developments due to the challenging goals, which still need to be successfully addressed at many levels, e.g., data decoding and processing, miniaturization, mechanical compliance, and robustness, data communication. Tactile sensing has developed rapidly over the past three decades but high-impact breakthroughs in application domains have to be successfully achieved.

Artificial tactile sensing is a still a relevant challenge, as it involves numerous research areas. Application domains include humanoid and industrial robotics, prosthetics, biomedical instrumentation, health care, bionics, robotics, virtual reality, haptic devices, IoT, cyber physical systems, virtual reality, and arts, to name but a few.

The aim of this Topical Collection is to foster submissions on research and achievements in the broad field of tactile sensors and sensing e.g. from materials up to systems and applications. We invite original contributions, so that current research trends can be presented in this collection.

Prof. Dr. Maurizio Valle
Collection 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 collection 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

  • innovative structural and sensing materials
  • manufacturing technology
  • novel tactile sensors
  • flexible, conformable, and stretchable sensors and arrays
  • electronic interface
  • artificial and electronic skin
  • tactile data processing and interpretation
  • innovative applications
  • haptic devices
  • touch-based human–robot interaction
  • tactile and visual sensing integration
  • tactile Internet
  • tactile sensing in prosthetics, neuro-rehabilitation, neuro- and bio-engineering, consumer goods, arts, IoT

Published Papers (2 papers)

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2023

Jump to: 2022

15 pages, 1879 KiB  
Article
Exploring Tactile Temporal Features for Object Pose Estimation during Robotic Manipulation
by Viral Rasik Galaiya, Mohammed Asfour, Thiago Eustaquio Alves de Oliveira, Xianta Jiang  and Vinicius Prado da Fonseca
Sensors 2023, 23(9), 4535; https://doi.org/10.3390/s23094535 - 06 May 2023
Cited by 1 | Viewed by 1586
Abstract
Dexterous robotic manipulation tasks depend on estimating the state of in-hand objects, particularly their orientation. Although cameras have been traditionally used to estimate the object’s pose, tactile sensors have recently been studied due to their robustness against occlusions. This paper explores tactile data’s [...] Read more.
Dexterous robotic manipulation tasks depend on estimating the state of in-hand objects, particularly their orientation. Although cameras have been traditionally used to estimate the object’s pose, tactile sensors have recently been studied due to their robustness against occlusions. This paper explores tactile data’s temporal information for estimating the orientation of grasped objects. The data from a compliant tactile sensor were collected using different time-window sample sizes and evaluated using neural networks with long short-term memory (LSTM) layers. Our results suggest that using a window of sensor readings improved angle estimation compared to previous works. The best window size of 40 samples achieved an average of 0.0375 for the mean absolute error (MAE) in radians, 0.0030 for the mean squared error (MSE), 0.9074 for the coefficient of determination (R2), and 0.9094 for the explained variance score (EXP), with no enhancement for larger window sizes. This work illustrates the benefits of temporal information for pose estimation and analyzes the performance behavior with varying window sizes, which can be a basis for future robotic tactile research. Moreover, it can complement underactuated designs and visual pose estimation methods. Full article
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2022

Jump to: 2023

16 pages, 4453 KiB  
Article
Tactile Pressure Sensors Calibration with the Use of High Pressure Zones
by Petr Zvyagin
Sensors 2022, 22(19), 7290; https://doi.org/10.3390/s22197290 - 26 Sep 2022
Viewed by 1910
Abstract
A simple and cost-effective calibration procedure for piezoresistive ink tactile pressure sensors is crucial for their use in geotechnical research applications. Such a procedure should be applicable in field conditions and require a minimum amount of equipment. The paper describes a new method [...] Read more.
A simple and cost-effective calibration procedure for piezoresistive ink tactile pressure sensors is crucial for their use in geotechnical research applications. Such a procedure should be applicable in field conditions and require a minimum amount of equipment. The paper describes a new method for calibrating tactile pressure sensors with 8-bit sensels’ output. The method is based on the approximation of a single sensel output and consideration of multiple calibration patches. The advantage of the developed method is using local high-pressure zones in calibration patches. The developed method has been successfully applied in calibration of two 5051-350 Tekscan sensors by means of three dead weights: 2 kg, 5 kg and 10 kg. One calibrated sensor was new, and another one had been previously used in the harsh environment of the ice tank in the experiment with model ice. The calibration curves for these two sensors did not reveal a significant difference. For 72% of the 150 obtained load patches in calibration, the absolute discrepancy of actual and calibrated load occurred to be less than 5%. Full article
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