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Electronics
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Human-Robot Interaction and Applications: Challenges and Future Perspectives
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Human-Robot Interaction and Applications: Challenges and Future Perspectives

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 8426

Special Issue Editors

Prof. Dr. Bipin Indurkhya

E-Mail Website
Guest Editor
Cognitive Science Department, Jagiellonian University, 31-007 Krakow, Poland
Interests: cognitive science; cognitive robotics; intelligent system for multimodal human–computer interaction
Dr. Eleuda Nuñez

E-Mail Website
Guest Editor
Center for Cybernics Research, University of Tsukuba, Ibaraki 305-8577, Japan
Interests: human-centered computing; haptic devices; computational models of human behavior; interaction design studies
Prof. Dr. Marie-Monique Schaper

E-Mail Website
Guest Editor
Department for Computer Engineering and Digital Design, Universitat de Lleida, 25006 Lleida, Spain
Interests: educational robotics; embodied interaction; computing education; design research; participatory design

Special Issue Information

Dear Colleagues,

The emergence of new technologies and application areas in human–robot interaction is having significant and meaningful impacts on the ways people experience and interact with the world. This Special Issue sheds light on challenges in the design and use of robots and intelligent systems in our everyday life. Furthermore, this Special Issue invites scholars to critically reflect on the future perspectives of this research field.

We encourage the following types of submissions (among others):

  • Design studies or evaluative research that highlight how the features of robots and intelligent systems are intended to support people’s engagement, learning, and behaviors in everyday life.
  • Critical, sociological, and/or methodological articles on the opportunities/challenges of designing/using intelligent technology in this field.
  • Towards the development of empathic machines: understanding and modeling human behavior to create machines that can respond to and understand humans at an emotional level.
  • Affective haptics: sensors and/or actuators designed to support human–robot interaction through touch.
  • Ethnographic and cultural topics related to human–robot interaction.
  • Calm-technology approach to human–robot interaction.
  • In-the-wild and field studies on human–robot interaction.
  • Child–robot interaction.
  • Infant–robot interaction.

Prof. Dr. Bipin Indurkhya
Dr. Eleuda Nuñez
Prof. Dr. Marie-Monique Schaper
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

  • affective haptics
  • calm technology
  • child–robot interaction
  • co-design
  • empathetic HRI
  • ethnographic studies on HRI
  • infant–robot interaction
  • multimodal HRI
  • participatory design

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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Further information on MDPI's Special Issue policies can be found here.

Published Papers (6 papers)

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Research

26 pages, 5529 KiB  
Article
Statistically Informed Multimodal (Domain Adaptation by Transfer) Learning Framework: A Domain Adaptation Use-Case for Industrial Human–Robot Communication
by Debasmita Mukherjee and Homayoun Najjaran
Electronics 2025, 14(7), 1419; https://doi.org/10.3390/electronics14071419 - 31 Mar 2025
Viewed by 217
Abstract
Cohesive human–robot collaboration can be achieved through seamless communication between human and robot partners. We posit that the design aspects of human–robot communication (HRCom) can take inspiration from human communication to create more intuitive systems. A key component of HRCom systems is perception [...] Read more.
Cohesive human–robot collaboration can be achieved through seamless communication between human and robot partners. We posit that the design aspects of human–robot communication (HRCom) can take inspiration from human communication to create more intuitive systems. A key component of HRCom systems is perception models developed using machine learning. Being data-driven, these models suffer from the dearth of comprehensive, labelled datasets while models trained on standard, publicly available datasets do not generalize well to application-specific scenarios. Complex interactions and real-world variability lead to shifts in data that require domain adaptation by the models. Existing domain adaptation techniques do not account for incommensurable modes of communication between humans and robot perception systems. Taking into account these challenges, a novel framework is presented that leverages existing domain adaptation techniques off-the-shelf and uses statistical measures to start and stop the training of models when they encounter domain-shifted data. Statistically informed multimodal (domain adaptation by transfer) learning (SIMLea) takes inspiration from human communication to use human feedback to auto-label for iterative domain adaptation. The framework can handle incommensurable multimodal inputs, is mode and model agnostic, and allows statistically informed extension of datasets, leading to more intuitive and naturalistic HRCom systems. Full article
(This article belongs to the Special Issue Human-Robot Interaction and Applications: Challenges and Future Perspectives)
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24 pages, 259 KiB  
Article
How Do Older Adults Perceive Technology and Robots? A Participatory Study in a Care Center in Poland
by Paulina Zguda, Zuzanna Radosz-Knawa, Tymon Kukier, Mikołaj Radosz, Alicja Kamińska and Bipin Indurkhya
Electronics 2025, 14(6), 1106; https://doi.org/10.3390/electronics14061106 - 11 Mar 2025
Viewed by 690
Abstract
One of the key areas of application for social robots is healthcare, particularly for the elderly. To better address user needs, a study involving the humanoid robot NAO was conducted at the Municipal Care Center in Krakow, Poland, with the participation of 29 [...] Read more.
One of the key areas of application for social robots is healthcare, particularly for the elderly. To better address user needs, a study involving the humanoid robot NAO was conducted at the Municipal Care Center in Krakow, Poland, with the participation of 29 older adults. This participatory design study explored their attitudes toward robots and technology both before and after interacting with the robot. It also identified the most desirable applications of social robots that could simplify everyday life for the elderly. Full article
(This article belongs to the Special Issue Human-Robot Interaction and Applications: Challenges and Future Perspectives)
21 pages, 1178 KiB  
Article
User Behavior on Value Co-Creation in Human–Computer Interaction: A Meta-Analysis and Research Synthesis
by Xiaohong Chen and Yuan Zhou
Electronics 2025, 14(6), 1071; https://doi.org/10.3390/electronics14061071 - 7 Mar 2025
Viewed by 601
Abstract
Value co-creation in online communities refers to a process in which all participants within a platform’s ecosystem exchange and integrate resources while engaging in mutually beneficial interactive processes to generate perceived value-in-use. User behavior plays a crucial role in influencing value co-creation in [...] Read more.
Value co-creation in online communities refers to a process in which all participants within a platform’s ecosystem exchange and integrate resources while engaging in mutually beneficial interactive processes to generate perceived value-in-use. User behavior plays a crucial role in influencing value co-creation in human–computer interaction. However, existing research contains controversies, and there is a lack of comprehensive studies exploring which factors of user behavior influence it and the mechanisms through which they operate. This paper employs meta-analysis to examine the factors and mechanisms based on 42 studies from 2006 to 2023 with a sample size of 30,016. It examines the relationships at the individual, interaction, and environment layers and explores moderating effects through subgroup analysis. The results reveal a positive overall effect between user behavior and value co-creation performance. Factors including self-efficacy, social identity, enjoyment, and belonging (individual layer); information support, social interaction, trust, and reciprocity (interaction layer); as well as shared values, incentives, community culture, and subjective norms (environment layer) positively influence value co-creation. The moderating effect of situational and measurement factors indicates that Chinese communities and monocultural environments have more significant effects than international and multicultural ones, while community type is not significant. Structural equation models and subjective collaboration willingness have a stronger moderating effect than linear regression and objective behavior, which constitutes a counterintuitive finding. This study enhances theoretical research on user behavior and provides insights for managing value co-creation in human–computer interaction. Full article
(This article belongs to the Special Issue Human-Robot Interaction and Applications: Challenges and Future Perspectives)
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14 pages, 1900 KiB  
Article
Combining Genetic Algorithm with Local Search Method in Solving Optimization Problems
by Velin Kralev and Radoslava Kraleva
Electronics 2024, 13(20), 4126; https://doi.org/10.3390/electronics13204126 - 20 Oct 2024
Cited by 2 | Viewed by 1626
Abstract
This research is focused on evolutionary algorithms, with genetic and memetic algorithms discussed in more detail. A graph theory problem related to finding a minimal Hamiltonian cycle in a complete undirected graph (Travelling Salesman Problem—TSP) is considered. The implementations of two approximate algorithms [...] Read more.
This research is focused on evolutionary algorithms, with genetic and memetic algorithms discussed in more detail. A graph theory problem related to finding a minimal Hamiltonian cycle in a complete undirected graph (Travelling Salesman Problem—TSP) is considered. The implementations of two approximate algorithms for solving this problem, genetic and memetic, are presented. The main objective of this study is to determine the influence of the local search method versus the influence of the genetic crossover operator on the quality of the solutions generated by the memetic algorithm for the same input data. The results show that when the number of possible Hamiltonian cycles in a graph is increased, the memetic algorithm finds better solutions. The execution time of both algorithms is comparable. Also, the number of solutions that mutated during the execution of the genetic algorithm exceeds 50% of the total number of all solutions generated by the crossover operator. In the memetic algorithm, the number of solutions that mutate does not exceed 10% of the total number of all solutions generated by the crossover operator, summed with those of the local search method. Full article
(This article belongs to the Special Issue Human-Robot Interaction and Applications: Challenges and Future Perspectives)
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17 pages, 7640 KiB  
Article
Research on Designing Context-Aware Interactive Experiences for Sustainable Aging-Friendly Smart Homes
by Yi Lu, Lejia Zhou, Aili Zhang, Mengyao Wang, Shan Zhang and Minghua Wang
Electronics 2024, 13(17), 3507; https://doi.org/10.3390/electronics13173507 - 4 Sep 2024
Cited by 3 | Viewed by 2381
Abstract
With the advancement of artificial intelligence, the home care environment for elderly users is becoming increasingly intelligent and systematic. The context aware human–computer interaction technology of sustainable aging-friendly smart homes can effectively identify user needs, enhance energy efficiency, and optimize resource utilization, thereby [...] Read more.
With the advancement of artificial intelligence, the home care environment for elderly users is becoming increasingly intelligent and systematic. The context aware human–computer interaction technology of sustainable aging-friendly smart homes can effectively identify user needs, enhance energy efficiency, and optimize resource utilization, thereby improving the convenience and sustainability of smart home care services. This paper reviews literature and analyzes cases to summarize the background and current state of context-aware interaction experience research in aging-friendly smart homes. Targeting solitary elderly users aged 60–74, the study involves field observations and user interviews to analyze their characteristics and needs, and to summarize the interaction design principles for aging-friendly smart homes. We explore processes for context-aware and methods for identifying user behaviors, emphasizing the integration of green, eco-friendly, and energy-saving principles in the design process. Focusing on the living experience and quality of life for elderly users living alone, this paper constructs a context-aware user experience model based on multimodal interaction technology. Using elderly falls as a case example, we design typical scenarios for aging-friendly smart homes from the perspectives of equipment layout and innovative hardware and software design. The goal is to optimize the home care experience for elderly users, providing theoretical and practical guidance for smart home services in an aging society. Ultimately, the study aims to develop safer, more convenient, and sustainable home care solutions. Full article
(This article belongs to the Special Issue Human-Robot Interaction and Applications: Challenges and Future Perspectives)
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20 pages, 629 KiB  
Article
Lessons in Developing a Behavioral Coding Protocol to Analyze In-the-Wild Child–Robot Interaction Events and Experiments
by Xela Indurkhya and Gentiane Venture
Electronics 2024, 13(7), 1175; https://doi.org/10.3390/electronics13071175 - 22 Mar 2024
Cited by 1 | Viewed by 1658
Abstract
Behavioral analyses of in-the-wild HRI studies generally rely on interviews or visual information from videos. This can be very limiting in settings where video recordings are not allowed or limited. We designed and tested a vocalization-based protocol to analyze in-the-wild child–robot interactions based [...] Read more.
Behavioral analyses of in-the-wild HRI studies generally rely on interviews or visual information from videos. This can be very limiting in settings where video recordings are not allowed or limited. We designed and tested a vocalization-based protocol to analyze in-the-wild child–robot interactions based upon a behavioral coding scheme utilized in wildlife biology, specifically in studies of wild dolphin populations. The audio of a video or audio recording is converted into a transcript, which is then analyzed using a behavioral coding protocol consisting of 5–6 categories (one indicating non-robot-related behavior, and 4–5 categories of robot-related behavior). Refining the code categories and training coders resulted in increased agreement between coders, but only to a level of moderate reliability, leading to our recommendation that it be used with three coders to assess where there is majority consensus, and thereby correct for subjectivity. We discuss lessons learned in the design and implementation of this protocol and the potential for future child–robot experiments analyzed through vocalization behavior. We also perform a few observational behavior analyses from vocalizations alone to demonstrate the potential of this field. Full article
(This article belongs to the Special Issue Human-Robot Interaction and Applications: Challenges and Future Perspectives)
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