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Intelligent Robotics: Design and Applications
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Intelligent Robotics: Design and Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 20 June 2025 | Viewed by 6396

Special Issue Editors

Prof. Dr. Yen-Ting Lin

E-Mail Website
Guest Editor
Department of Computer Science and Artificial Intelligence, National Pingtung University, Pingtung, Taiwan
Interests: intelligent and expert systems; educational technology; artificial intelligence; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Yi-Chun Lin

E-Mail Website
Guest Editor
Department of Information Management, R. O. C. Military Academy, Kaohsiung City 830, Taiwan
Interests: artificial intelligent; data engineering; information education; digital marketing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the advancement of information technology, especially the rapid development of artificial intelligence technology in recent years, the era of intelligent robots is booming. The demand for intelligent robots in various fields is increasing, such as education, healthcare, finance, catering, tourism, manufacturing, and transportation. This also allows intelligent robots to be designed and developed in a variety of forms, including virtual and physical intelligent robots. For example, Khan Academy uses ChatGPT to develop a virtual AI Tutor, and hotels use physical intelligent robots to provide check-in and baggage delivery services for guests. In addition, intelligent robots have also had a huge impact on the promotion of SDGs.

In order to promote the development of intelligent robot design and application, this special issue invites scholars and researchers in related fields to jointly present research results on the topic of "Intelligent Robotics: Design and Applications". This special issue welcomes but is not limited to the following topics for paper submission:

  • Design and application of virtual/physical intelligent robots in professional fields
  • Design and application of virtual/physical intelligent robots in life fields
  • Human-robot interaction
  • Machine learning and artificial intelligence for robotics
  • Collaborative robots/cobots
  • Intelligent robots for SDGs
  • Self-training and learning of intelligent robots
  • Generative AI for rototics
  • Collective and social robots

Prof. Dr. Yen-Ting Lin
Dr. Yi-Chun Lin
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. Applied Sciences 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

  • intelligent robots
  • virtual/physical robots
  • human-robot interaction
  • artificial intelligence
  • machine learning

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Published Papers (4 papers)

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Research

16 pages, 1851 KiB  
Article
Stakeholder Perspectives on Safety Issues in Collaborative Mobile Robots: A Case Study of Quadruped Robot Applications in a Smart Factory
by Eutteum Go, Jun Hyoung Lee, So Yeong Kim, Jong Sup Lee, Hyung Hwan Kim and Joong Yeon Lim
Appl. Sci. 2024, 14(22), 10232; https://doi.org/10.3390/app142210232 - 7 Nov 2024
Viewed by 1777
Abstract
With the development of Industry 4.0, collaborative mobile robots are becoming increasingly prevalent in industrial settings, raising important safety considerations in human–robot interaction environments. This study examines the safety issues in collaborative mobile robotics through a case study of a smart factory utilizing [...] Read more.
With the development of Industry 4.0, collaborative mobile robots are becoming increasingly prevalent in industrial settings, raising important safety considerations in human–robot interaction environments. This study examines the safety issues in collaborative mobile robotics through a case study of a smart factory utilizing quadruped robots. This research aims to contribute to the development of safety management strategies by identifying potential risk factors and analyzing the differences in risk perception among stakeholders. A survey was conducted among 93 operators in the factory to identify the main risk factors, followed by a Delphi study with four groups of experts: robot operators, safety management experts, robot developers, and academic experts. The Kruskal–Wallis and Mann–Whitney U tests were used to analyze the statistical significance of differences in perception between the groups. The results showed that collision and deviation from the path were the most concerning risk factors. Significant differences were found in the perceptions of several hazards between expert groups, with academic experts rating most hazards highly while robot developers rated them relatively low. The findings highlight how background knowledge and experience influence risk perception in collaborative robotics. These varying perspectives should be considered when developing safety management strategies for mobile robots in industrial settings, suggesting the importance of multi-stakeholder collaboration and targeted educational programs. Full article
(This article belongs to the Special Issue Intelligent Robotics: Design and Applications)
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16 pages, 41641 KiB  
Article
Survival 1.0: A Novel Autonomous Industrial Mobile Warehouse (AIMW) for Industrial Environments
by Eduardo Garcia, Miguel Montaña and Nicolás Montés
Appl. Sci. 2024, 14(21), 9781; https://doi.org/10.3390/app14219781 - 25 Oct 2024
Viewed by 931
Abstract
This article presents the design, implementation and start-up of the first AIMW (Autonomous Industrial Mobile Warehouse) in the industry, in particular, in the factory located at Ford España S.L. in Almussafes (Valencia). This first version has been given the name of “Survival”, due [...] Read more.
This article presents the design, implementation and start-up of the first AIMW (Autonomous Industrial Mobile Warehouse) in the industry, in particular, in the factory located at Ford España S.L. in Almussafes (Valencia). This first version has been given the name of “Survival”, due to its ability to survive the industrial environment commonly known as “the jungle”. The motivation for the design of the first AIMW was due to the management of spare warehouses for maintenance tasks. In all factories there is a central warehouse where replacement materials with a higher probability of use are placed near the warehouse exit, thus reducing the time to obtain the replacement. However, in large factories, such as automobile manufacturing, the distance between the central warehouse and the place where the breakdown occurs may cause very long delays. For this reason, there are smaller warehouses distributed throughout the plant that replicate the part of the central warehouse where the most used materials are kept. The objective of our research is to make that part of the central warehouse mobile with the AIMW design, thus eliminating the fixed warehouses. In the factory at Ford España S.L. in Almussafes there are 170 of these warehouses distributed in a homogeneous way. In this first proposal of an AIMW, and with the primary objective of reducing costs, Survival 1.0 has been designed based on a commercial AMR. For its choice, commercial AMRs were tested in real situations within the Ford factory (Almussafes). As a result, none of them were able to pass all the tests. In addition, the current regulations for AMRs, the ANSI/ITSDF B56.5:2019 and the EN 1525:1997 standard, only define minimum test standards to describe how manufacturers and users must carry out the safety measurements of AGVs and AMRs. However, from an industry point of view, these regulations are not adequate. Therefore, there are extensions of these regulations generated by the companies themselves that imply additional developments of commercial AMRs. This paper shows the developments made to be able to integrate the first AIMW into the production line, but it also shows the gap between research and standardization of AMRs with respect to the demands and needs of the industry. There are currently three Survival 1.0 AIMWs in operation in the factory at Ford España S.L. in Almussafes. Full article
(This article belongs to the Special Issue Intelligent Robotics: Design and Applications)
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17 pages, 1593 KiB  
Article
Synthesis of Non-Linguistic Utterances for Sound Design Support Using a Genetic Algorithm
by Ahmed Khota, Eric W. Cooper and Yu Yan
Appl. Sci. 2024, 14(11), 4572; https://doi.org/10.3390/app14114572 - 26 May 2024
Viewed by 1384
Abstract
As social robots become more prevalent, they often employ non-speech sounds, in addition to other modes of communication, to communicate emotion and intention in an increasingly complex visual and audio environment. These non-speech sounds are usually tailor-made, and research into the generation of [...] Read more.
As social robots become more prevalent, they often employ non-speech sounds, in addition to other modes of communication, to communicate emotion and intention in an increasingly complex visual and audio environment. These non-speech sounds are usually tailor-made, and research into the generation of non-speech sounds that can convey emotions has been limited. To enable social robots to use a large amount of non-speech sounds in a natural and dynamic way, while expressing a wide range of emotions effectively, this work proposes an automatic method of sound generation using a genetic algorithm, coupled with a random forest model trained on representative non-speech sounds to validate each produced sound’s ability to express emotion. The sounds were tested in an experiment wherein subjects rated the perceived valence and arousal. Statistically significant clusters of sounds in the valence arousal space corresponded to different emotions, showing that the proposed method generates sounds that can readily be used in social robots. Full article
(This article belongs to the Special Issue Intelligent Robotics: Design and Applications)
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20 pages, 2604 KiB  
Article
Digital-Twin-Based System for Foam Cleaning Robots in Spent Fuel Pools
by Manhua Li, Fubin Chen and Wuyun Zhou
Appl. Sci. 2024, 14(5), 2020; https://doi.org/10.3390/app14052020 - 29 Feb 2024
Cited by 2 | Viewed by 1467
Abstract
This paper introduces a digital-twin-based system for foam cleaning robots in spent fuel pools, aiming to efficiently clean foam in spent fuel pools. The system adopts a four-layer architecture, including the physical entity layer, twin data layer, twin model layer, and application service [...] Read more.
This paper introduces a digital-twin-based system for foam cleaning robots in spent fuel pools, aiming to efficiently clean foam in spent fuel pools. The system adopts a four-layer architecture, including the physical entity layer, twin data layer, twin model layer, and application service layer. Initially, the robot was modeled in two dimensions, encompassing physical and kinematic aspects. Subsequently, data collection and fusion were carried out using laser radar and depth cameras, establishing a virtual model of the working scenario and mapping the physical entity to the digital twin model. Building upon this foundation, improvements were made in applying the full-coverage path planning algorithm by integrating a pure tracking algorithm, thereby enhancing the cleaning efficiency. Obstacle detection and localization were conducted using infrared and depth cameras positioned above the four corners of the spent fuel pool, with the digital twin platform transmitting coordinates to the robot for obstacle avoidance operations. Finally, comparative experiments were conducted on the robot’s full-coverage algorithm, along with simulation experiments on the robot’s position and motion direction. The experimental results indicated that this approach reduced the robot’s overall cleaning time and energy consumption. Furthermore, it enabled motion data detection for the digital twin robot, reducing the risk of collisions during the cleaning process and providing insights and directions for the intelligent development of foam cleaning robots. Full article
(This article belongs to the Special Issue Intelligent Robotics: Design and Applications)
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