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Sensing for Social and Intelligent Robots

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

Deadline for manuscript submissions: 20 June 2024 | Viewed by 801

Special Issue Editor


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Guest Editor
Department of Robot and Smart System Engineering, Kyungpook National University, Daegu 41566, Republic of Korea
Interests: artificial intelligence; intelligent robot; emotional robot; natural language processing

Special Issue Information

Dear Colleagues,

Social and intelligent robots have gained significant attention due to their potential to revolutionize various domains, including healthcare, education, entertainment, and assistive technology. Sensing technologies play a vital role in enabling these robots to perceive and understand their surroundings, interact with humans, and exhibit adaptive behaviors.

This Special Issue invites researchers and practitioners to contribute original research papers, reviews, case studies, and application-focused articles that cover a broad range of topics related to sensing for social and intelligent robots, including, but not limited to, the following:

  • Sensing modalities for social robots (e.g., vision, audio, touch, and proximity);
  • The perception and recognition of human gestures, emotions, and expressions;
  • Human–robot interaction and collaboration using sensing technologies;
  • Sensor fusion techniques for multimodal perception in robots;
  • Adaptive and context-aware sensing for intelligent robots;
  • Machine learning and artificial intelligence in robotic perception and behavior;
  • Sensor-based navigation and mapping for social robots;
  • Sensing for assistive and healthcare robotics;
  • Ethical considerations and privacy issues in sensing for social robots;
  • Evaluation and benchmarking methodologies for sensing technologies in social robotics.

Authors are encouraged to present their original research contributions, experimental results, and practical applications related to sensing technologies in social and intelligent robots. All submissions will undergo a rigorous peer-review process to ensure the publication of high-quality and impactful research.

Prof. Dr. Bo-Yeong Kang
Guest Editor

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
  • intelligent robots
  • human–robot interaction
  • sensor fusion
  • assistive and healthcare robotics

Published Papers (1 paper)

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Research

19 pages, 620 KiB  
Article
A Mood Semantic Awareness Model for Emotional Interactive Robots
by Tiehua Zhou, Zihan Yu, Ling Wang and Keun Ho Ryu
Sensors 2024, 24(3), 845; https://doi.org/10.3390/s24030845 - 28 Jan 2024
Viewed by 571
Abstract
The rapid development of natural language processing technology and improvements in computer performance in recent years have resulted in the wide-scale development and adoption of human–machine dialogue systems. In this study, the Icc_dialogue model is proposed to enhance the semantic awareness of moods [...] Read more.
The rapid development of natural language processing technology and improvements in computer performance in recent years have resulted in the wide-scale development and adoption of human–machine dialogue systems. In this study, the Icc_dialogue model is proposed to enhance the semantic awareness of moods for emotional interactive robots. Equipped with a voice interaction module, emotion calculation is conducted based on model responses, and rules for calculating users’ degree of interest are formulated. By evaluating the degree of interest, the system can determine whether it should transition to a new topic to maintain the user’s interest. This model can also address issues such as overly purposeful responses and rigid emotional expressions in generated replies. Simultaneously, this study explores topic continuation after answering a question, the construction of dialogue rounds, keyword counting, and the creation of a target text similarity matrix for each text in the dialogue dataset. The matrix is normalized, weights are assigned, and the final text score is calculated. In the text with the highest score, the content of dialogue continuation is determined by calculating a subsequent sentence with the highest similarity. This resolves the issue in which the conversational bot fails to continue dialogue on a topic after answering a question, instead waiting for the user to voluntarily provide more information, resulting in topic interruption. As described in the experimental section, both automatic and manual evaluations were conducted to validate the significant improvement in the mood semantic awareness model’s performance in terms of dialogue quality and user experience. Full article
(This article belongs to the Special Issue Sensing for Social and Intelligent Robots)
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