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Advanced Systems for Human Machine Interactions

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

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 14295

Special Issue Editor


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Guest Editor
Faculty of Mechanical Engineering, University of Ljubljana, Ljubljana, Slovenia
Interests: artificial intelligence; machine vision; control theory

Special Issue Information

Dear Colleagues,

Machines have been an important part of human life since the first industrial revolution. Recently, however, they have become a part of our lives in way that could hardly be imagined even a couple of decades ago. Concepts such as the Internet of Things, Artificial Intelligence, Machine Vision, 5G networks, etc. are pointing toward a future where machines and humans will become even more connected. A very important part of this process are human–machine interface (HMI) systems. As they are the part the human most often comes in contact with when dealing with machines, their design is very important and can often make the difference between certain applications being accepted among users or not.

In this Special Issue titled “Advanced Systems for Human–Machine Interactions”, we aim to provide a collection of papers that present the latest research in all areas of human–machine interactions for various applications. The Special Issue solicits submissions from scientists and engineers, whose work represents a novel contribution to the field of HMI. The articles that this issue is looking for must be original work or comprehensive reviews, which should not be published or submitted for publication to any other journal. Topics of interest include but are not limited to the following:

  • Machine vision;
  • Artificial intelligence;
  • Advanced sensorial systems;
  • Physiological sensing;
  • Collaborative robotics.

Prof. Primož Podržaj
Guest Editor

Manuscript Submission Information

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Published Papers (4 papers)

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Research

19 pages, 4521 KiB  
Article
A Wearable IMU System for Flexible Teleoperation of a Collaborative Industrial Robot
by Gašper Škulj, Rok Vrabič and Primož Podržaj
Sensors 2021, 21(17), 5871; https://doi.org/10.3390/s21175871 - 31 Aug 2021
Cited by 20 | Viewed by 4279
Abstract
Increasing the accessibility of collaborative robotics requires interfaces that support intuitive teleoperation. One possibility for an intuitive interface is offered by wearable systems that measure the operator’s movement and use the information for robot control. Such wearable systems should preserve the operator’s movement [...] Read more.
Increasing the accessibility of collaborative robotics requires interfaces that support intuitive teleoperation. One possibility for an intuitive interface is offered by wearable systems that measure the operator’s movement and use the information for robot control. Such wearable systems should preserve the operator’s movement capabilities and, thus, their ability to flexibly operate in the workspace. This paper presents a novel wireless wearable system that uses only inertial measurement units (IMUs) to determine the orientation of the operator’s upper body parts. An algorithm was developed to transform the measured orientations to movement commands for an industrial collaborative robot. The algorithm includes a calibration procedure, which aligns the coordinate systems of all IMUs, the operator, and the robot, and the transformation of the operator’s relative hand motions to the movement of the robot’s end effector, which takes into account the operator’s orientation relative to the robot. The developed system is demonstrated with an example of an industrial application in which a workpiece needs to be inserted into a fixture. The robot’s motion is compared between the developed system and a standard robot controller. The results confirm that the developed system is intuitive, allows for flexible control, and is robust enough for use in industrial collaborative robotic applications. Full article
(This article belongs to the Special Issue Advanced Systems for Human Machine Interactions)
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35 pages, 5846 KiB  
Article
Family-Centered Design: Interactive Performance Testing and User Interface Evaluation of the Slovenian eDavki Public Tax Portal
by Jure Trilar, Tjaša Sobočan and Emilija Stojmenova Duh
Sensors 2021, 21(15), 5161; https://doi.org/10.3390/s21155161 - 30 Jul 2021
Cited by 5 | Viewed by 3471
Abstract
This is the latest article in a series of research on the family-centered design concept. The theoretical context was revisited and expounded to support its usefulness in conjunction with a user-centered design approach within distinct application domains. A very important contribution is applied [...] Read more.
This is the latest article in a series of research on the family-centered design concept. The theoretical context was revisited and expounded to support its usefulness in conjunction with a user-centered design approach within distinct application domains. A very important contribution is applied through the development of the instruments—website capture, a public testing platform, results processing and the Web Content Accessibility Guide 2.1 recommendation tool—to conduct unmoderated remote testing of user interfaces that corresponds to the requirements of general digitalization efforts as well as the response to current and future health risks. With this set of instruments, an experiment was conducted to address the differences in usage, and performance-wise and user-based evaluation methods, of the eDavki public tax portal, among two generations, adults and elderly citizens, and between an original and an adapted user interface that respects accessibility and other recommendations. The differences found are further discussed and are congruent to particularities that have been modified within interfaces. Full article
(This article belongs to the Special Issue Advanced Systems for Human Machine Interactions)
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16 pages, 5415 KiB  
Article
An Instrument for the Characterization and Calibration of Optical Sensors
by Enrico Gastasini, Niccolò Capecci, Francesco Lupi, Alessio Gagliardi, Sergio Saponara and Michele Lanzetta
Sensors 2021, 21(15), 5141; https://doi.org/10.3390/s21155141 - 29 Jul 2021
Cited by 5 | Viewed by 3138
Abstract
This paper presents the development of a hardware/software system for the characterization of the electronic response of optical (camera) sensors such as matrix and linear color and monochrome Charge Coupled Device (CCD) or Complementary Metal Oxide Semiconductor (CMOS). The electronic response of a [...] Read more.
This paper presents the development of a hardware/software system for the characterization of the electronic response of optical (camera) sensors such as matrix and linear color and monochrome Charge Coupled Device (CCD) or Complementary Metal Oxide Semiconductor (CMOS). The electronic response of a sensor is required for inspection purposes. It also allows the design and calibration of the integrating device to achieve the desired performance. The proposed instrument equipment fulfills the most recent European Machine Vision Association (EMVA) 1288 standard ver. 3.1: the spatial non uniformity of the illumination ΔE must be under 3%, and the sensor must achieve an f-number of 8.0 concerning the light source. The following main innovations have achieved this: an Ulbricht sphere providing a uniform light distribution (irradiation) of 99.54%; an innovative illuminator with proper positioning of color Light Emitting Diodes (LEDs) and control electronics; and a flexible C# program to analyze the sensor parameters, namely Quantum Efficiency, Overall System Gain, Temporal Dark Noise, Dark Signal Non Uniformity (DSNU1288), Photo Response Non-Uniformity (PRNU1288), Maximum achievable Signal to Noise Ratio (SNRmax), Absolute sensitivity threshold, Saturation Capacity, Dynamic Range, and Dark Current. This new instrument has allowed a camera manufacturer to design, integrate, and inspect numerous devices and camera models (Necta, Celera, and Aria). Full article
(This article belongs to the Special Issue Advanced Systems for Human Machine Interactions)
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24 pages, 9143 KiB  
Article
Augmenting Around-Device Interaction by Geomagnetic Field Built-in Sensor Utilization
by Sandi Ljubic, Franko Hržić, Alen Salkanovic and Ivan Štajduhar
Sensors 2021, 21(9), 3087; https://doi.org/10.3390/s21093087 - 28 Apr 2021
Viewed by 2639
Abstract
In this paper, we investigate the possibilities for augmenting interaction around the mobile device, with the aim of enabling input techniques that do not rely on typical touch-based gestures. The presented research focuses on utilizing a built-in magnetic field sensor, whose readouts are [...] Read more.
In this paper, we investigate the possibilities for augmenting interaction around the mobile device, with the aim of enabling input techniques that do not rely on typical touch-based gestures. The presented research focuses on utilizing a built-in magnetic field sensor, whose readouts are intentionally affected by moving a strong permanent magnet around a smartphone device. Different approaches for supporting magnet-based Around-Device Interaction are applied, including magnetic field fingerprinting, curve-fitting modeling, and machine learning. We implemented the corresponding proof-of-concept applications that incorporate magnet-based interaction. Namely, text entry is achieved by discrete positioning of the magnet within a keyboard mockup, and free-move pointing is enabled by monitoring the magnet’s continuous movement in real-time. The related solutions successfully expand both the interaction language and the interaction space in front of the device without altering its hardware or involving sophisticated peripherals. A controlled experiment was conducted to evaluate the provided text entry method initially. The obtained results were promising (text entry speed of nine words per minute) and served as a motivation for implementing new interaction modalities. The use of neural networks has shown to be a better approach than curve fitting to support free-move pointing. We demonstrate how neural networks with a very small number of input parameters can be used to provide highly usable pointing with an acceptable level of error (mean absolute error of 3 mm for pointer position on the smartphone display). Full article
(This article belongs to the Special Issue Advanced Systems for Human Machine Interactions)
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