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Intelligent Social Robotic Systems
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Intelligent Social Robotic Systems

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

Deadline for manuscript submissions: 1 October 2024 | Viewed by 6408

Special Issue Editors

Dr. Ameersing Luximon

E-Mail Website
Guest Editor
EMEDS Limited, Kowloon, Hong Kong
Interests: social robots; ergonomics in design; wearable products; design
Prof. Dr. Ravindra S. Goonetilleke

E-Mail Website
Guest Editor
Department of Industrial and Systems Engineering, Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates
Interests: human-centered product and service design; human–computer interaction; psychophysical modelling; data visualization

Special Issue Information

Dear Colleagues,

Intelligent robots are widely used in industries; however, with development of ubiquitous mobile technologies, virtual presence and communication networks, and enhanced AI systems, there has been a shift in the trend and development of intelligent robots, one of them being the development of social robots. Social robots are not only found in the realms of science fiction, but also reality. Although we tend to envision social robots to be similar to us, with a head and human-like features, with the development of technology, information systems, AI systems, smart cities, and smart homes, social robots can take different forms and shapes. In addition, the way we interact with robots in general is evolving, as there is progressively more acceptance of robots in people lives. Social robots enable interactions between humans, other robots, and smart systems. Recently, due to COVID-19, there has been an increased use of social robots to greet and provide customer services. Furthermore, with the aging population, it is anticipated that social robots will be widely used in health care and service sectors for active aging. 

The development of intelligent and smart social robots is faced with many challenges in terms of the design; interaction with humans; data collection; instrumentation and sensing technologies; AI technologies; and communication with other smart systems and social robots. Social robot challenges are evolving as the users adapt to the availability of smart systems. This Special Issue focuses mainly on intelligent robots with an emphasis on social robots; however, it is not limited to purely that topic. Any research in terms of instrumentation, sensing, visualization, design, interaction, data analysis, modelling, and applications of robots in business, public, or private settings will be considered. Well written research papers on design concepts, the future of social robots, surveys, and the literature will also be considered. 

Dr. Ameersing Luximon
Prof. Dr. Ravindra S. Goonetilleke
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. Sensors 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 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

  • social robots: past, present, and future
  • theoretical aspects of robotic systems, including sensing and instrumentation
  • robotics systems and technology
  • wearables technology and systems for social robots
  • AI technologies in intelligent robotic systems
  • human–robot interaction
  • design of intelligent social robotic systems
  • intelligent robotic systems in everyday life
  • instrumentation and sensors for intelligent robotic systems
  • smart homes with social systems
  • smart cities and social robots
  • social robots in health care

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Published Papers (3 papers)

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22 pages, 4641 KiB  
Article
Social Type-Aware Navigation Framework for Mobile Robots in Human-Shared Environments
by Sumin Kang, Sungwoo Yang, Daewon Kwak, Yura Jargalbaatar and Donghan Kim
Sensors 2024, 24(15), 4862; https://doi.org/10.3390/s24154862 - 26 Jul 2024
Viewed by 482
Abstract
As robots become increasingly common in human-populated environments, they must be perceived as social beings and behave socially. People try to preserve their own space during social interactions with others, and this space depends on a variety of factors, such as individual characteristics [...] Read more.
As robots become increasingly common in human-populated environments, they must be perceived as social beings and behave socially. People try to preserve their own space during social interactions with others, and this space depends on a variety of factors, such as individual characteristics or their age. In real-world social spaces, there are many different types of people, and robots need to be more sensitive, especially when interacting with vulnerable subjects such as children. However, the current navigation methods do not consider these differences and apply the same avoidance strategies to everyone. Thus, we propose a new navigation framework that considers different social types and defines appropriate personal spaces for each, allowing robots to respect them. To this end, the robot needs to classify people in a real environment into social types and define the personal space for each type as a Gaussian asymmetric function to respect them. The proposed framework is validated through simulations and real-world experiments, demonstrating that the robot can improve the quality of interactions with people by providing each individual with an adaptive personal space. The proposed costmap layer is available on GitHub. Full article
(This article belongs to the Special Issue Intelligent Social Robotic Systems)
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22 pages, 2326 KiB  
Article
NEP+: A Human-Centered Framework for Inclusive Human-Machine Interaction Development
by Enrique Coronado, Natsuki Yamanobe and Gentiane Venture
Sensors 2023, 23(22), 9136; https://doi.org/10.3390/s23229136 - 12 Nov 2023
Cited by 1 | Viewed by 2070
Abstract
This article presents the Network Empower and Prototyping Platform (NEP+), a flexible framework purposefully crafted to simplify the process of interactive application development, catering to both technical and non-technical users. The name "NEP+" encapsulates the platform’s dual mission: to empower the network-related capabilities [...] Read more.
This article presents the Network Empower and Prototyping Platform (NEP+), a flexible framework purposefully crafted to simplify the process of interactive application development, catering to both technical and non-technical users. The name "NEP+" encapsulates the platform’s dual mission: to empower the network-related capabilities of ZeroMQ and to provide software tools and interfaces for prototyping and integration. NEP+ accomplishes this through a comprehensive quality model and an integrated software ecosystem encompassing middleware, user-friendly graphical interfaces, a command-line tool, and an accessible end-user programming interface. This article primarily focuses on presenting the proposed quality model and software architecture, illustrating how they can empower developers to craft cross-platform, accessible, and user-friendly interfaces for various applications, with a particular emphasis on robotics and the Internet of Things (IoT). Additionally, we provide practical insights into the applicability of NEP+ by briefly presenting real-world user cases where human-centered projects have successfully utilized NEP+ to develop robotics systems. To further emphasize the suitability of NEP+ tools and interfaces for developer use, we conduct a pilot study that delves into usability and workload assessment. The outcomes of this study highlight the user-friendly features of NEP+ tools, along with their ease of adoption and cross-platform capabilities. The novelty of NEP+ fundamentally lies in its holistic approach, acting as a bridge across diverse user groups, fostering inclusivity, and promoting collaboration. Full article
(This article belongs to the Special Issue Intelligent Social Robotic Systems)
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17 pages, 1475 KiB  
Article
Socially-Assistive Robots to Support Learning in Students on the Autism Spectrum: Investigating Educator Perspectives and a Pilot Trial of a Mobile Platform to Remove Barriers to Implementation
by David Silvera-Tawil, Susan Bruck, Yi Xiao and DanaKai Bradford
Sensors 2022, 22(16), 6125; https://doi.org/10.3390/s22166125 - 16 Aug 2022
Cited by 6 | Viewed by 2891
Abstract
Technology offers educators tools that can tailor learning to students’ learning styles and interests. Research into the use of socially-assistive robots as a learning support for children on the autism spectrum are showing promising results. However, to date, few schools have introduced these [...] Read more.
Technology offers educators tools that can tailor learning to students’ learning styles and interests. Research into the use of socially-assistive robots as a learning support for children on the autism spectrum are showing promising results. However, to date, few schools have introduced these robots to support learning in students on the autism spectrum. This paper reports on a research project that investigated the barriers to implementing socially-assistive robot supported learning, and the expectations, perceived benefits and concerns of school teachers and therapists of students on the autism spectrum and adults on the autism spectrum. First, three focus groups were conducted with six adults on the autism spectrum, and 13 teachers and therapists of students from two autism-specific schools. During the focus groups, there was cautious optimism from participants about the value of socially-assistive robots for teaching support. While the data showed that participants were in favour of trialling socially-assistive robots in the classroom, they also raised several concerns and potential barriers to implementation, including the need for teacher training. In response to their concerns, the second part of the project focussed on developing a software platform and mobile application (app) to support the introduction of robots into autism-specific classrooms. The software platform and app were then trialled in two schools (n = 7 teachers and therapists). Results from focus groups indicated that participants believe socially-assistive robots could be useful for learning support, as the mobile app provides an easy to use tool to support preparing and conducting lessons that would motivate them to trial robots in the classroom. Full article
(This article belongs to the Special Issue Intelligent Social Robotic Systems)
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