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Electronics
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New Advances in Human-Robot Collaboration
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New Advances in Human-Robot Collaboration

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

Deadline for manuscript submissions: 15 December 2024 | Viewed by 2528

Special Issue Editors

Prof. Dr. Daniela M. Romano

E-Mail Website
Guest Editor
Department of Information Studies, University College London, London WC1E 6BT, UK
Interests: human–robot interaction; artificial intelligence; application of human–robot collaboration in all fields
Special Issues, Collections and Topics in MDPI journals
Dr. Bangli Liu

E-Mail Website
Guest Editor
Institute of Artificial Intelligence, De Montfort University, Leicester LE3 5LX, UK
Interests: artificial intelligence; human behaviour analysis and applications; human–robot interaction; computer vision; deep learning

Special Issue Information

Dear Colleagues,

Human-robot collaboration (HRC) refers to integrating human and robot capabilities in a collaborative working environment. It has the potential to revolutionise manufacturing, healthcare monitoring, logistics, education, space exploration, and more, resulting in advancements across various domains.

For example, robots can support medical professionals in healthcare by performing repetitive tasks, such as medication delivery or patient monitoring, allowing healthcare providers to focus on more complex and critical aspects of care. HRC can also enhance rehabilitation processes by providing physical assistance and real-time patient feedback during therapy sessions. In manufacturing, HRC enables robots to assist humans in assembly tasks, leading to increased productivity, improved quality, and reduced physical strain on workers. In education, they can support children’s activities and enhance students’ social interaction.

Recent years have seen a significant increase in the prevalence of human-robot collaboration, largely attributed to the rapid advancements in AI technologies. However, applications in HRC have not yet been extensively studied.

We are pleased to invite experts from academia and industry to present their recent developments integrating human and robot capabilities in a collaborative working environment

This Special Issue aims to overcome this challenge by inviting experts from academia and industry to present their recent developments. In this Special Issue, original research articles and reviews are welcome.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Human-robot interaction;
  • Human-robot collaboration;
  • Robot perception;
  • Applications of artificial intelligence;
  • Human activity/intention analysis;
  • Computer vision;
  • AI-driven wearable sensors;
  • Smart sensing;
  • Application of human-robot collaboration in all fields;
  • Healthcare monitoring systems;
  • Disease diagnosis.

We look forward to receiving your contributions.

Prof. Dr. Daniela M. Romano
Dr. Bangli Liu
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-robot interaction
  • human-robot collaboration
  • robot perception
  • applications of artificial intelligence
  • human activity/intention analysis
  • computer vision
  • AI-driven wearable sensors
  • smart sensing
  • application of human-robot collaboration in all fields
  • healthcare monitoring systems
  • disease diagnosis

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

Published Papers (2 papers)

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Research

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20 pages, 11064 KiB  
Article
The Adaptive Bilateral Control of Underwater Manipulator Teleoperation System with Uncertain Parameters and External Disturbance
by Jianjun Zhang, Manjiang Xia, Shasha Li, Zhiqiang Liu and Jinxian Yang
Electronics 2024, 13(6), 1122; https://doi.org/10.3390/electronics13061122 - 19 Mar 2024
Cited by 2 | Viewed by 993
Abstract
A novel self-adaptive bilateral control strategy is introduced to manage uncertainties inherent in the teleoperation of an underwater manipulator system effectively. In response to uncertainties stemming from both the mathematical model and external disturbances, our approach offers innovative solutions. Firstly, to address uncertainties [...] Read more.
A novel self-adaptive bilateral control strategy is introduced to manage uncertainties inherent in the teleoperation of an underwater manipulator system effectively. In response to uncertainties stemming from both the mathematical model and external disturbances, our approach offers innovative solutions. Firstly, to address uncertainties in the master model parameters, we propose a reference adaptive impedance control based on a nominal model. This control strategy dynamically adjusts the reference position of the desired model, leveraging adaptive control laws to compensate for model uncertainties. Additionally, to tackle uncertainties specific to the slave manipulator, we employ adaptive compensation using radial basis function (RBF) networks. Our unique combination of sliding mode variable structure controllers and robust adaptive controllers aims to mitigate approximation errors, ensuring precise tracking of the master manipulator’s position by the slave manipulator. By employing Lyapunov function analysis, we demonstrate the system’s superior tracking performance and global stability, with assured asymptotic convergence for force–position tracking. Through comprehensive experimentation, our results showcase the exceptional force–position tracking capabilities of the overall control system, even under challenging conditions of model uncertainties and external disturbances. Moreover, our system exhibits remarkable stability, reliability, and robustness, underscoring the effectiveness of our proposed adaptive control approach. Full article
(This article belongs to the Special Issue New Advances in Human-Robot Collaboration)
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Review

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20 pages, 2054 KiB  
Review
Using Social Robotics to Identify Educational Behavior: A Survey
by Antonio J. Romero-C. de Vaca, Roberto Angel Melendez-Armenta and Hiram Ponce
Electronics 2024, 13(19), 3956; https://doi.org/10.3390/electronics13193956 - 8 Oct 2024
Viewed by 832
Abstract
The advancement of social robots in recent years has opened a promising avenue for providing users with more accessible and personalized attention. These robots have been integrated into various aspects of human life, particularly in activities geared toward students, such as entertainment, education, [...] Read more.
The advancement of social robots in recent years has opened a promising avenue for providing users with more accessible and personalized attention. These robots have been integrated into various aspects of human life, particularly in activities geared toward students, such as entertainment, education, and companionship, with the assistance of artificial intelligence (AI). AI plays a crucial role in enhancing these experiences by enabling social and educational robots to interact and adapt intelligently to their environment. In social robotics, AI is used to develop systems capable of understanding human emotions and responding to them, thereby facilitating interaction and collaboration between humans and robots in social settings. This article aims to present a survey of the use of robots in education, highlighting the degree of integration of social robots in this field worldwide. It also explores the robotic technologies applied according to the students’ educational level. This study provides an overview of the technical literature in social robotics and behavior recognition systems applied to education at various educational levels, especially in recent years. Additionally, it reviews the range of social robots in the market involved in these activities. The objects of study, techniques, and tools used, as well as the resources and results, are described to offer a view of the current state of the reviewed areas and to contribute to future research. Full article
(This article belongs to the Special Issue New Advances in Human-Robot Collaboration)
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