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Advances in Bio-Inspired Skin-Like Sensor Technologies
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Advances in Bio-Inspired Skin-Like Sensor Technologies

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

Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 14360

Special Issue Editors

Dr. Tareq Assaf

E-Mail Website
Guest Editor
Department of Electronic and Electrical Engineering, University of Bath, Bath, UK
Interests: bio-inspired robotics; bio-inspired sensing; soft robotics; modular robotics
Dr. Uriel Martinez-Hernandez

E-Mail Website
Guest Editor
Department of Electronic and Electrical Engineering, University of Bath, Bath, UK
Interests: robotics; human–robot Interaction; tactile perception; multimodal wearable robots; assistive robotics; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

An artificial sense of touch is key to enhancing the capabilities of robotic platforms, and this area of study is continuously growing and expanding. The artificial sense of touch allows the performance of highly skilled tasks and is largely employed in object exploration, manipulation, and interfaces such as touch pads. However, the sense of touch extends far beyond the hands, fingertips, and haptics. Artificial skin covering a robot body will allow a new level of spatial awareness. This is essential to allow autonomous systems to move confidently and safely while interacting with the surrounding environment. Enhanced safety not only allows robots and humans to interact in the same space, but also allows robots to be safe moving in unstructured environments full of obstacles and dangers that were designed for humans, and even for operation in hazardous environments.

In recent decades, advances in materials and sensing technology have allowed researchers to develop a number of advanced tactile technologies despite a multitude of difficulties. These tactile systems, mounted on the hands, fingers, torsos, and bodies of a variety of robotics systems, offer effective bio-inspired solutions for the advancement of skilled tasks such as human–robot interaction and autonomous robot exploration.

This Special Issue of Sensors focuses on those solutions, techniques, and technologies that are tackling artificial tactile sensing. These include bio-inspired solutions, large- and small-scale concepts, hands, skin, and fingertip devices. Related application-specific solutions to provide spatial awareness to robotic platforms are also within the scope of this Special Issue.

Dr. Tareq Assaf
Dr. Uriel Martinez-Hernandez
Guest Editors

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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

  • tactile sensing
  • artificial skin systems
  • spatial awareness
  • tactile pads
  • processing strategies for tactile sensors

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Published Papers (4 papers)

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Research

16 pages, 3723 KiB  
Article
Using Novel Multi-Frequency Analysis Methods to Retrieve Material and Temperature Information in Tactile Sensing Areas
by Mehdi Abdelwahed, Lounis Zerioul, Alexandre Pitti and Olivier Romain
Sensors 2022, 22(22), 8876; https://doi.org/10.3390/s22228876 - 17 Nov 2022
Cited by 5 | Viewed by 2020
Abstract
This article presents a novel artificial skin technology based on the Electric Impedance Tomography (EIT) that employs multi-frequency currents for detecting the material and the temperature of objects in contact with piezoresistive sheets. To date, few artificial skins in the literature are capable [...] Read more.
This article presents a novel artificial skin technology based on the Electric Impedance Tomography (EIT) that employs multi-frequency currents for detecting the material and the temperature of objects in contact with piezoresistive sheets. To date, few artificial skins in the literature are capable of detecting an object’s material, e.g., wood, skin, leather, or plastic. EIT-based artificial skins have been employed mostly to detect the position of the contact but not its characteristics. Thanks to multi-frequency currents, our EIT-based artificial skin is capable of characterising the spectral profile of objects in contact and identifying an object’s material at ambient temperature. Moreover, our model is capable of detecting several levels of temperature (from −10 up to 60 °C) and can also maintain a certain accuracy for material identification. In addition to the known capabilities of EIT-based artificial skins concerning detecting pressure and location of objects, as well as being low cost, these two novel modalities demonstrate the potential of EIT-based artificial skins to achieve global tactile sensing. Full article
(This article belongs to the Special Issue Advances in Bio-Inspired Skin-Like Sensor Technologies)
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14 pages, 2459 KiB  
Article
Neuromorphic Tactile Edge Orientation Classification in an Unsupervised Spiking Neural Network
by Fraser L. A. Macdonald, Nathan F. Lepora, Jörg Conradt and Benjamin Ward-Cherrier
Sensors 2022, 22(18), 6998; https://doi.org/10.3390/s22186998 - 15 Sep 2022
Cited by 8 | Viewed by 2898
Abstract
Dexterous manipulation in robotic hands relies on an accurate sense of artificial touch. Here we investigate neuromorphic tactile sensation with an event-based optical tactile sensor combined with spiking neural networks for edge orientation detection. The sensor incorporates an event-based vision system (mini-eDVS) into [...] Read more.
Dexterous manipulation in robotic hands relies on an accurate sense of artificial touch. Here we investigate neuromorphic tactile sensation with an event-based optical tactile sensor combined with spiking neural networks for edge orientation detection. The sensor incorporates an event-based vision system (mini-eDVS) into a low-form factor artificial fingertip (the NeuroTac). The processing of tactile information is performed through a Spiking Neural Network with unsupervised Spike-Timing-Dependent Plasticity (STDP) learning, and the resultant output is classified with a 3-nearest neighbours classifier. Edge orientations were classified in 10-degree increments while tapping vertically downward and sliding horizontally across the edge. In both cases, we demonstrate that the sensor is able to reliably detect edge orientation, and could lead to accurate, bio-inspired, tactile processing in robotics and prosthetics applications. Full article
(This article belongs to the Special Issue Advances in Bio-Inspired Skin-Like Sensor Technologies)
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14 pages, 6011 KiB  
Article
PhotoElasticFinger: Robot Tactile Fingertip Based on Photoelastic Effect
by Dinmukhammed Mukashev, Nurdaulet Zhuzbay, Ainur Koshkinbayeva, Bakhtiyar Orazbayev and Zhanat Kappassov
Sensors 2022, 22(18), 6807; https://doi.org/10.3390/s22186807 - 8 Sep 2022
Cited by 6 | Viewed by 2914
Abstract
The sense of touch is fundamental for a one-to-one mapping between the environment and a robot that physically interacts with the environment. Herein, we describe a tactile fingertip design that can robustly detect interaction forces given data collected from a camera. This design [...] Read more.
The sense of touch is fundamental for a one-to-one mapping between the environment and a robot that physically interacts with the environment. Herein, we describe a tactile fingertip design that can robustly detect interaction forces given data collected from a camera. This design is based on the photoelastic effect observed in silicone matter. Under the force applied to the silicone rubber, owing to the stress-induced birefringence, the light propagating within the silicone rubber is subjected to the angular phase shift, where the latter is proportional to the increase in the image brightness in the camera frames. We present the calibration and test results of the photoelastic sensor design on a bench using a robot arm and with a certified industrial force torque sensor. We also discuss the applications of this sensor design and its potential relationship with human mechano-transduction receptors. We achieved a force sensing range of up to 8 N with a force resolution of around 0.5 N. The photoelastic tactile fingertip is suitable for robot grasping and might lead to further progress in robust tactile sensing. Full article
(This article belongs to the Special Issue Advances in Bio-Inspired Skin-Like Sensor Technologies)
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Graphical abstract

13 pages, 30616 KiB  
Article
VibroTouch: Active Tactile Sensor for Contact Detection and Force Sensing via Vibrations
by Danissa Sandykbayeva, Zhanat Kappassov and Bakhtiyar Orazbayev
Sensors 2022, 22(17), 6456; https://doi.org/10.3390/s22176456 - 27 Aug 2022
Cited by 10 | Viewed by 5508
Abstract
Accurate and fast contact detection between a robot manipulator and objects is crucial for safe robot–object and human–robot interactions. Traditional collision detection techniques relied on force–torque sensors and Columb friction cone estimation. However, the strain gauges used in the conventional force sensors require [...] Read more.
Accurate and fast contact detection between a robot manipulator and objects is crucial for safe robot–object and human–robot interactions. Traditional collision detection techniques relied on force–torque sensors and Columb friction cone estimation. However, the strain gauges used in the conventional force sensors require low-noise and high-precision electronics to deliver the signal to the final user. The Signal-to-Noise Ratio (SNR) in these devices is still an issue in light contact detection. On the other hand, the Eccentric Rotating Mass (ERM) motors are very sensitive to subtle touch as their vibrating resonant state loses immediately. The vibration, in this case, plays a core role in triggering the tactile event. This project’s primary goal is to use generated and received vibrations to establish the scope of object properties that can be obtained through low-frequency generation on one end and Fourier analysis of the accelerometer data on the other end. The main idea behind the system is the phenomenon of change in vibration propagation patterns depending on the grip properties. Moreover, the project’s original aim is to gather enough information on vibration feedback on objects of various properties and compare them. These data sets are further analyzed in terms of frequency and applied grip force correlations in order to prepare the ground for pattern extraction and recognition based on the physical properties of an object. Full article
(This article belongs to the Special Issue Advances in Bio-Inspired Skin-Like Sensor Technologies)
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