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Electronics
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Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics
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Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (15 July 2024) | Viewed by 29557

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Juan Ernesto Solanes Galbis

E-Mail Website
Guest Editor
Instituto de Diseño y Fabricación, Universitat Politècnica de València, 46022 Valencia, Spain
Interests: virtual reality; augmented reality; robotics; control and automation; human–machine interaction
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Luis Gracia

E-Mail Website
Guest Editor
Instituto IDF, Universitat Politecnica de Valencia, 46022 Valencia, Spain
Interests: robotic systems; system modeling and control; robust control
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jaime Valls Miro

E-Mail Website
Guest Editor
Centre for Autonomous Systems, University of Technology Sydney, Sydney, NSW 2007, Australia
Interests: robotics; perception; planning; HRI; industry projects

Special Issue Information

Dear Colleagues,

We cordially invite you to submit original research or review articles to the journal Electronics for the Special Issue entitled “Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics”.

Human–machine interaction allows the exchange of information and collaboration between human beings and intelligent machine systems. The success of this interaction is due to many factors, including the naturalness with which the user receives information from the machine and its environment, the ease with which the user collaborates with the machine, the simplicity of the interfaces or devices used for the interaction, and the manner that benefits are found from both the abilities of human and the capabilities of the machine.

From an industrial point of view, human–machine interaction opens the possibility of improving current processes by means of a real collaboration between workers and automatic systems. In this sense, human–machine interaction gives rise to new industrial solutions in which workers and machines work closely to improve the ergonomics and safety of workers, as well as the efficiency of the production lines and the quality of the resulting products.

Therefore, this Special Issue welcomes the submission of technical, experimental, and methodological papers related to human–machine interaction. Moreover, special attention will be given to innovative approaches, strategies, and applications developed to improve current industrial processes.

Potential topics include, but are not limited to, the following:

  • Human–machine interfaces;
  • Human–robot collaboration;
  • Augmented reality applications;
  • Virtual reality applications;
  • Development of human–robot devices;
  • Haptic feedback applications;
  • Human–robot control design;
  • Human–computer interaction;
  • Human–machine communication;
  • Implementation of collaborative robotics systems;
  • Simulation of human–robot interaction in stochastic scenarios;
  • Artificial intelligence applied to the industry;
  • Real-time simulation of digital twins;
  • Implementation of extended reality interfaces for industrial applications;
  • Development of robot feedback controllers;
  • Development and validation of industrial metaverses;
  • Big data analytics;
  • Industrial management;
  • Logistics.

Prof. Dr. Juan Ernesto Solanes Galbis
Prof. Dr. Luis Gracia
Prof. Dr. Jaime Valls Miro
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 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. Electronics 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 2400 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

  • human–machine interfaces
  • human–robot collaboration
  • augmented reality applications
  • virtual reality applications
  • development of human–robot devices
  • haptic feedback applications
  • human–robot control design
  • human–computer interaction
  • human–machine communication
  • smart industry

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (12 papers)

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Editorial

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5 pages, 181 KiB  
Editorial
Advances in Human–Machine Interaction, Artificial Intelligence, and Robotics
by Juan Ernesto Solanes, Luis Gracia and Jaime Valls Miro
Electronics 2024, 13(19), 3856; https://doi.org/10.3390/electronics13193856 - 29 Sep 2024
Viewed by 784
Abstract
The convergence of artificial intelligence (AI), robotics, and immersive technologies such as augmented reality (AR), virtual reality (VR), and extended reality (XR) is transforming the way humans interact with machines [...] Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)

Research

Jump to: Editorial

23 pages, 15789 KiB  
Article
Design and Development of Shadow: A Cost-Effective Mobile Social Robot for Human-Following Applications
by Alejandro Torrejón, Noé Zapata, Lucas Bonilla, Pablo Bustos and Pedro Núñez
Electronics 2024, 13(17), 3444; https://doi.org/10.3390/electronics13173444 - 30 Aug 2024
Cited by 1 | Viewed by 583
Abstract
This study explores the development and implementation of Shadow, an advanced mobile social robot designed to meet specific functional requirements. Shadow is intended to serve both as a versatile tool and a human companion, assisting in various tasks across different environments. The construction [...] Read more.
This study explores the development and implementation of Shadow, an advanced mobile social robot designed to meet specific functional requirements. Shadow is intended to serve both as a versatile tool and a human companion, assisting in various tasks across different environments. The construction emphasizes cost efficiency and high agility, utilizing 3D printing technology exclusively. The robot features omnidirectional kinematics and a flexible power electronics system, accommodating diverse energy needs with lithium batteries that ensure at least seven hours of autonomous operation. An integrated sensor array continuously monitors the power system, tracks tilt and acceleration, and facilitates self-diagnostic functions. Rapid prototyping allows for swift iteration, testing, and refinement to align with project goals. This paper provides a comprehensive blueprint for designing cost-effective, highly agile robots using advanced manufacturing techniques. Extensive testing, including stability and sensory skills evaluations, demonstrates Shadow’s adherence to its design objectives. Shadow has advanced from technology readiness level (TRL) 2 to TRL 7 within a year and is currently undergoing trials with advanced functionalities, offering significant insights into overcoming practical design challenges and optimizing robot functionality. Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)
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19 pages, 9299 KiB  
Article
Mission-Conditioned Path Planning with Transformer Variational Autoencoder
by Kyoungho Lee, Eunji Im and Kyunghoon Cho
Electronics 2024, 13(13), 2437; https://doi.org/10.3390/electronics13132437 - 21 Jun 2024
Viewed by 762
Abstract
This paper introduces a novel deep learning framework for robotic path planning that addresses two primary challenges: integrating mission specifications defined through Linear Temporal Logic (LTL) and enhancing trajectory quality via cost function integration within the configuration space. Our approach utilizes a Conditional [...] Read more.
This paper introduces a novel deep learning framework for robotic path planning that addresses two primary challenges: integrating mission specifications defined through Linear Temporal Logic (LTL) and enhancing trajectory quality via cost function integration within the configuration space. Our approach utilizes a Conditional Variational Autoencoder (CVAE) to efficiently encode optimal trajectory distributions, which are subsequently processed by a Transformer network. This network leverages mission-specific information from LTL formulas to generate control sequences, ensuring adherence to LTL specifications and the generation of near-optimal trajectories. Additionally, our framework incorporates an anchor control set—a curated collection of plausible control values. At each timestep, the proposed method selects and refines a control from this set, enabling precise adjustments to achieve desired outcomes. Comparative analysis and rigorous simulation testing demonstrate that our method outperforms both traditional sampling-based and other deep-learning-based path-planning techniques in terms of computational efficiency, trajectory optimality, and mission success rates. Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)
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17 pages, 10571 KiB  
Article
Methodical Approach to Proactivity Using a Digital Twin of Production Process
by Fedor Burčiar, Pavel Važan, Bohuslava Juhásová and Martin Juhás
Electronics 2023, 12(15), 3335; https://doi.org/10.3390/electronics12153335 - 4 Aug 2023
Cited by 1 | Viewed by 1113
Abstract
Real-time simulation and digital twin (DT) as a part of Industry 4.0 are becoming increasingly relevant, especially when considering production cycles. Most issues with production cycles arise from having a demand for customized production orders, while having nonmodular production lines with a medium-to-high [...] Read more.
Real-time simulation and digital twin (DT) as a part of Industry 4.0 are becoming increasingly relevant, especially when considering production cycles. Most issues with production cycles arise from having a demand for customized production orders, while having nonmodular production lines with a medium-to-high complexity in the decision-making process. All these conditions lead to a possibility of unpredictable consequences. Being able to predict behavior and possible failure scenarios before the production starts has proven to save both costs and time. With an introduction of a new ISO standard which is solely focused on DT creation and sets a starting point for future research, researchers are finally able to focus on creating DT prototypes built for specific scenarios while maintaining the core concepts. This paper focuses on proposing strategies for DT and real-time simulation integration into production cycles, based on the new standards, which can be generalized and applied on a multitude of different systems with minimal changes. The proposed solutions offer different levels of human interaction with the Human–Machine Interfaces used in Cyber–Physical Systems created as a part of DT. Applicability of the solution has been verified based on the results of experiments carried out on the WITNESS Horizon simulation platform with utilization of the custom Order Manipulation Interface (OMI) application. Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)
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29 pages, 8951 KiB  
Article
Robotic Cell Reliability Optimization Based on Digital Twin and Predictive Maintenance
by Dimitris Mourtzis, Sofia Tsoubou and John Angelopoulos
Electronics 2023, 12(9), 1999; https://doi.org/10.3390/electronics12091999 - 25 Apr 2023
Cited by 10 | Viewed by 2696
Abstract
Robotic systems have become a standard tool in modern manufacturing due to their unique characteristics, such as repeatability, precision, and speed, among others. One of the main challenges of robotic manipulators is the low degree of reliability. Low reliability increases the probability of [...] Read more.
Robotic systems have become a standard tool in modern manufacturing due to their unique characteristics, such as repeatability, precision, and speed, among others. One of the main challenges of robotic manipulators is the low degree of reliability. Low reliability increases the probability of disruption in manufacturing processes, minimizing in this way the productivity and by extension the profit of the company. To address the abovementioned challenges, this research work proposes a robotic cell reliability optimization method based on digital twin and predictive maintenance. Concretely, the simulation of the robot is provided, and emphasis is given to the reliability optimization of the robotic cell’s critical component. A supervised machine learning model is trained, aiming to detect and classify the faulty behavior of the critical component. Furthermore, a framework is proposed for the remaining useful life prediction with the aim to improve the reliability of the robotic cell. Thus, following the results of the current research work, appropriate maintenance tasks can be applied, preventing the robotic cell from serious failures and ensuring high reliability. Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)
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14 pages, 861 KiB  
Article
Toward Adaptive Human–Robot Collaboration for the Inclusion of People with Disabilities in Manual Labor Tasks
by Nils Mandischer, Marius Gürtler, Carlo Weidemann, Elodie Hüsing, Stefan-Octavian Bezrucav, Daniel Gossen, Vincent Brünjes, Mathias Hüsing and Burkhard Corves
Electronics 2023, 12(5), 1118; https://doi.org/10.3390/electronics12051118 - 24 Feb 2023
Cited by 7 | Viewed by 2173
Abstract
While human–robot collaboration is already integrated in industrial and service robotics applications, it is only used with able-bodied workers. However, collaboration through assistive robots is a major driver toward the inclusion of people with disabilities, which was demonstrated in recent research projects. Currently, [...] Read more.
While human–robot collaboration is already integrated in industrial and service robotics applications, it is only used with able-bodied workers. However, collaboration through assistive robots is a major driver toward the inclusion of people with disabilities, which was demonstrated in recent research projects. Currently, inclusive robot workplaces have to be customized toward the work process and the individual needs of the person. Within, robots act along a fixed schedule and are not able to adapt to changes within the process or the needs of the interacting person. Hence, such workplaces are expensive and unappealing for companies of the first labor market, and do not realize the full potential of the technology. In this work, we propose a generalized approach toward the inclusion of people with disabilities with collaborative robots. To this end, we propose a system that analyzes the in situ capabilities of a person using a two-stage reasoning approach. The methodology is based on an ontology that allows the matchmaking of individual capabilities with process requirements. Capabilities are modeled in two time frames, through which fast (e.g., fatigue) and slow effects (e.g., worsening of illness) become distinguishable. The matchmaking is used in task allocation to establish high-level control over the assistive system. By this approach, inclusive workplaces become autonomously adaptive to the in situ capabilities of the individual person, without the need for customization. Therefore, collaborative workplaces become not only inclusive, but a contributor toward a labor market for all. Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)
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17 pages, 2161 KiB  
Article
User Engagement Comparison between Advergames and Traditional Advertising Using EEG: Does the User’s Engagement Influence Purchase Intention?
by Ivonne Angelica Castiblanco Jimenez, Juan Sebastian Gomez Acevedo, Elena Carlotta Olivetti, Federica Marcolin, Luca Ulrich, Sandro Moos and Enrico Vezzetti
Electronics 2023, 12(1), 122; https://doi.org/10.3390/electronics12010122 - 27 Dec 2022
Cited by 23 | Viewed by 3803
Abstract
In the context of human–computer interaction (HCI), understanding user engagement (UE) while interacting with a product or service can provide valuable information for enhancing the design process. UE has been a priority research theme within HCI, as it assesses the user experience by [...] Read more.
In the context of human–computer interaction (HCI), understanding user engagement (UE) while interacting with a product or service can provide valuable information for enhancing the design process. UE has been a priority research theme within HCI, as it assesses the user experience by studying the individual’s behavioral response to some stimulus. Many studies looking to quantify the UE are available; however, most use self-report methods that rely only on participants’ answers. This study aims to explore a non-traditional method, specifically electroencephalography, to analyze users’ engagement while interacting with an advergame, an interactive form of advertising in video games. We aim to understand if a more interactive type of advertising will enhance the UE and whether, at the same time, it would influence the user’s purchase intention (UPI). To do this, we computed and compared the UE during the interaction with an advergame and a conventional TV commercial while measuring the participants’ brain activity. After the interaction with both types of advertising, the UPI was also evaluated. The findings demonstrate that a more interactive advertisement increased the participants’ UE and that, in most cases, a UE increment positively influenced the UPI. This study shows an example of the potential of physiological feedback applications to explore the users’ perceptions during and after the human–product interaction. The findings show how physiological methods can be used along with traditional ones for enhancing the UE analysis and provide helpful information about the advantages of engagement measurement in HCI applications. Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)
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13 pages, 5824 KiB  
Article
Convolutional Network Research for Defect Identification of Productor Appearance Surface
by Xu Xie and Xizhong Shen
Electronics 2022, 11(24), 4218; https://doi.org/10.3390/electronics11244218 - 18 Dec 2022
Cited by 2 | Viewed by 1907
Abstract
The accurate and rapid identification of surface defects is an important element of product appearance quality evaluation, and the application of deep learning for surface defect recognition is an ongoing hot topic. In this paper, a lightweight KD-EG-RepVGG network based on structural reparameterization [...] Read more.
The accurate and rapid identification of surface defects is an important element of product appearance quality evaluation, and the application of deep learning for surface defect recognition is an ongoing hot topic. In this paper, a lightweight KD-EG-RepVGG network based on structural reparameterization is designed for the identification of surface defects on strip steel as an example. In order to improve the stability and accuracy in the recognition of strip steel surface defects, an efficient attention network was introduced into the network, and then a Gaussian error linear activation function was applied in order to prevent the neurons from being set to zero during neural network training, leaving neuron parameters without being updated. Finally, knowledge distillation is used to transfer the knowledge of the RepVGG-A0 network to give the lightweight model better accuracy and generalization capability. The outcomes of the experiments indicate that the model has a computational and parametric volume of 22.3 M and 0.14 M, respectively, in the inference phase, a defect recognition accuracy of 99.44% on the test set, and a single image detection speed of 2.4 ms, making it more suitable for deployment in real engineering environments. Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)
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15 pages, 733 KiB  
Article
Technological Acceptance of Industry 4.0 by Students from Rural Areas
by Mauricio Castillo-Vergara, Alejandro Álvarez-Marín, Eduardo Villavicencio Pinto and Luis Enrique Valdez-Juárez
Electronics 2022, 11(14), 2109; https://doi.org/10.3390/electronics11142109 - 6 Jul 2022
Cited by 11 | Viewed by 3501
Abstract
In this study, our objective was to identify the factors that explain the acceptance of Industry 4.0 technologies by technical students. Industry 4.0 is made up of a series of technologies, such as the Internet of Things; cyber-physical systems; big data, data analytics, [...] Read more.
In this study, our objective was to identify the factors that explain the acceptance of Industry 4.0 technologies by technical students. Industry 4.0 is made up of a series of technologies, such as the Internet of Things; cyber-physical systems; big data, data analytics, or data mining; cloud computing or the cloud; augmented reality or mixed reality; additive manufacturing or 3D printing; cybersecurity; collaborative robots; artificial intelligence; 3D simulation; digital twin or digital twin; drones. We designed a theoretical model based on the technology acceptance model to explain the acceptance of these technologies. The study was carried out on a sample of 326 technical professional students. Students are considered ideal samples to test theoretical predictions regarding the relationships between variables in emerging technologies. The results show the positive effect of technological optimism on perceived usefulness and ease of use. However, there was not a direct effect on the attitude towards the use. A mediating effect was established. In addition, the facilitating conditions influence optimism and the ease of using the technology. These elements influence the attitude and intention to use, which is consistent with previous studies on technology acceptance. The results will guide the design of public policies to incorporate technologies into education. Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)
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15 pages, 2564 KiB  
Article
Toward Smart Communication Components: Recent Advances in Human and AI Speaker Interaction
by Hyejoo Kim, Sewoong Hwang, Jonghyuk Kim and Zoonky Lee
Electronics 2022, 11(10), 1533; https://doi.org/10.3390/electronics11101533 - 11 May 2022
Cited by 4 | Viewed by 2711
Abstract
This study aims to investigate how humans and artificial intelligence (AI) speakers interact and to examine the interactions based on three types of communication failures: system, semantic, and effectiveness. We divided service failures using AI speaker user data provided by the top telecommunication [...] Read more.
This study aims to investigate how humans and artificial intelligence (AI) speakers interact and to examine the interactions based on three types of communication failures: system, semantic, and effectiveness. We divided service failures using AI speaker user data provided by the top telecommunication service providers in South Korea and investigated the means to increase the continuity of product use for each type. We proved the occurrence of failure due to system error (H1) and negative results on sustainable use of the AI speaker due to not understanding the meaning (H2). It was observed that the number of users increases as the effectiveness failure rate increases. For single-person households constituted by persons in their 30s and 70s or older, the continued use of AI speakers was significant. We found that it alleviated loneliness and that human-machine interaction using AI speaker could reach a high level through a high degree of meaning transfer. We also expect AI speakers to play a positive role in single-person households, especially in cases of the elderly, which has become a tough challenge in the recent times. Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)
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21 pages, 3639 KiB  
Article
A Methodology to Produce Augmented-Reality Guided Tours in Museums for Mixed-Reality Headsets
by Ana Martí-Testón, Adolfo Muñoz, J. Ernesto Solanes, Luis Gracia and Josep Tornero
Electronics 2021, 10(23), 2956; https://doi.org/10.3390/electronics10232956 - 27 Nov 2021
Cited by 9 | Viewed by 3756
Abstract
In recent years, the use of technology in the museum context has changed radically. It has switched from the display of information to offering emotive, immersive, and rich experiences with heritage. Virtual interactive media have the potential to put museums back into a [...] Read more.
In recent years, the use of technology in the museum context has changed radically. It has switched from the display of information to offering emotive, immersive, and rich experiences with heritage. Virtual interactive media have the potential to put museums back into a relevant place in our increasingly digital society. The emergence of augmented-reality glasses offers the possibility to test and implement new methodologies compatible with this aim. However, most of the first examples developed in recent years did not take advantage of the possibilities of this new medium. This paper presents a novel methodology for producing mixed-reality applications for museums and heritage sites, with an intuitive, immersive, and natural way of operating. An experimental prototype designed for the archaeological museum of the Almoina is shown in the paper to demonstrate the benefits of the proposed system and methodology of production. In addition, the paper shows the results of several tests. Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)
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17 pages, 1296 KiB  
Article
Data-Driven Modelling of Human-Human Co-Manipulation Using Force and Muscle Surface Electromyogram Activities
by Ali Al-Yacoub, Myles Flanagan, Achim Buerkle, Thomas Bamber, Pedro Ferreira, Ella-Mae Hubbard and Niels Lohse
Electronics 2021, 10(13), 1509; https://doi.org/10.3390/electronics10131509 - 22 Jun 2021
Cited by 3 | Viewed by 2833
Abstract
With collaborative robots and the recent developments in manufacturing technologies, physical interactions between humans and robots represent a vital role in performing collaborative tasks. Most previous studies have focused on robot motion planning and control during the execution of the task. However, further [...] Read more.
With collaborative robots and the recent developments in manufacturing technologies, physical interactions between humans and robots represent a vital role in performing collaborative tasks. Most previous studies have focused on robot motion planning and control during the execution of the task. However, further research is required for direct physical contact for human-robot or robot-robot interactions, such as co-manipulation. In co-manipulation, a human operator manipulates a shared load with a robot through a semi-structured environment. In such scenarios, a multi-contact point with the environment during the task execution results in a convoluted force/toque signature that is difficult to interpret. Therefore, in this paper, a muscle activity sensor in the form of an electromyograph (EMG) is employed to improve the mapping between force/torque and displacements in co-manipulation tasks. A suitable mapping was identified by comparing the root mean square error amongst data-driven models, mathematical models, and hybrid models. Thus, a robot was shown to effectively and naturally perform the required co-manipulation with a human. This paper’s proposed hypotheses were validated using an unseen test dataset and a simulated co-manipulation experiment, which showed that the EMG and data-driven model improved the mapping of the force/torque features into displacements. Full article
(This article belongs to the Special Issue Advances in Human-Machine Interaction, Artificial Intelligence, and Robotics)
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