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Applied Sciences
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Robotics, Automation and Mechatronics (RAM): The Newest Technologies and Applications
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Robotics, Automation and Mechatronics (RAM): The Newest Technologies 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 October 2025 | Viewed by 1493

Special Issue Editors

Dr. Ionel Cristian Vladu

E-Mail Website
Guest Editor
Department of Electromechanics, Environment and Industrial Informatics, Faculty of Electrical Engineering, University of Craiova, 107 Decebal Blvd, Craiova, Romania
Interests: unconventional robots; smart materials; hyper-redundant robots; medical robots; robotics with bio-inspired designs; artificial inteligence
Prof. Dr. Costin Badica

E-Mail Website
Guest Editor
Department of Computers and Information Technology, Faculty of Automation, Computers and Electronics, University of Craiova, 107 Decebal Blvd, Craiova, Romania
Interests: artificial intelligence; multi-agent systems; software engineering; distributed systems; formal methods
Special Issues, Collections and Topics in MDPI journals
Dr. Ionuţ Daniel Geonea

E-Mail Website
Guest Editor
Department of Applied Mechanics and Civil Buildings, University of Craiova, Faculty of Mechanics, Str. Calea Bucuresti, nr. 107, Craiova, Dolj, România
Interests: robotics; robot design; mechatronics; walking robots, exoskeletons; design procedure; mechanics of machinery
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Nicu Bîzdoacă

E-Mail Website
Guest Editor
Department of Mechatronics and Robotics, Faculty of Automation, Computers and Electronics, University of Craiova, 107 Decebal Blvd, Craiova, Romania
Interests: smart material; virtual reality; nanotechnology; control
Special Issues, Collections and Topics in MDPI journals
Dr. Cristina Pană

E-Mail Website
Guest Editor Assistant
Department of Mechatronics and Robotics, Faculty of Automation, Computers and Electronics, University of Craiova, 107 Decebal Blvd, Craiova, Romania
Interests: robotics; mechatronics; automation; control; medical robotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is dedicated to the newest technologies and applications in the fields of Robotics, Automation, and Mechatronics (RAM). With the rapid advancements in these areas, there is a growing interest in developing and integrating cutting-edge technologies that enhance industrial processes, healthcare systems, and autonomous machines. This Special Issue focuses on the latest innovations in Robotics, Automation, and Mechatronics, encompassing a broad range of topics such as autonomous robotic systems, advanced automation frameworks, and intelligent mechatronic devices.

Contributions are encouraged in areas including, but not limited to, novel robotic designs, intelligent control systems, advanced automation algorithms, and the integration of AI in mechatronic systems. Emphasis will also be placed on topics such as sensor integration, machine learning for predictive maintenance, and optimization of autonomous systems. Articles related to the control, simulation, and optimization of robotic and mechatronic systems are also welcome, as are studies that explore the ethical implications of RAM technologies in industrial and healthcare applications. Studies in all areas related to this topic are welcome, such as, but not limited to, the following topics:

Robotics:

  • Human–robot symbiosis in cognitive robotics;
  • AI and machine learning in robotics;
  • Robotics in healthcare;
  • Robotic Process Automation (RPA) in industry;
  • Robotics in space exploration.

Automation:

  • Smart factories and Industry 4.0;
  • Industrial Internet of Things (IIoT) and automation;
  • Artificial intelligence in automation;
  • Cyber-physical systems;
  • Autonomous systems and vehicles.

Mechatronics:

  • Smart actuators and sensors in mechatronic systems;
  • Bio-mechatronics and wearable robotics;
  • Cyber-physical systems in mechatronics;
  • Micro-electro-mechanical systems;
  • Mechatronics in electric and autonomous vehicles.

Dr. Ionel Cristian Vladu
Prof. Dr. Costin Badica
Dr. Ionuţ Daniel Geonea
Prof. Dr. Nicu Bîzdoacă
Guest Editors

Dr. Cristina Pană
Guest Editor Assistant

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

  • robotics
  • automation
  • mechatronics
  • artificial intelligence (AI)
  • machine learning
  • autonomous systems
  • Industry 4.0
  • smart manufacturing
  • cyber-physical systems (CPS)
  • robotic process automation (RPA)
  • exoskeletons
  • humanoid robots
  • sensing and control systems
  • autonomous vehicles
  • intelligent systems

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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.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Published Papers (3 papers)

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Research

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24 pages, 6298 KiB  
Article
Design and Simulation of Mobile Robots Operating Within Networked Architectures Tailored for Emergency Situations
by Marco Mărieș and Mihai Olimpiu Tătar
Appl. Sci. 2025, 15(11), 6287; https://doi.org/10.3390/app15116287 - 3 Jun 2025
Viewed by 207
Abstract
This paper presents a simulation approach for mobile robots designed to operate within networks intended for emergency response scenarios. The simulation component is part of a broader and more complex system architecture focused on enhancing communication efficiency and operational coordination within robotic networks. [...] Read more.
This paper presents a simulation approach for mobile robots designed to operate within networks intended for emergency response scenarios. The simulation component is part of a broader and more complex system architecture focused on enhancing communication efficiency and operational coordination within robotic networks. This study leverages virtualization and robotic simulation technologies to develop a controlled environment in which the behavior and coordination of mobile robots can be analyzed and validated under simulated emergency conditions. To achieve this, a virtual machine was configured to host a ROS2 and Gazebo-based simulation environment. Custom packages were developed to enable the dynamic instantiation of mobile robots and the integration of essential sensing and control functionalities. The simulation process was carried out in two stages: initially, a single mobile robot was deployed and evaluated; subsequently, the configuration was extended to support a second robot, enabling multi-agent interaction within the simulated environment using flat surfaces. The proposed architecture demonstrates the potential for scalable deployment and simulation of mobile robotic instances. As a future direction, the authors aim to extend the system by optimizing data extraction from the simulation environment and implementing ROS2 microservices to facilitate secure and efficient communication with a centralized server deployed within a Kubernetes cluster. This integration will enable real-time coordination and data exchange between simulated agents and backend services, forming the foundation for a robust, distributed robotic system tailored to emergency operations. Full article
(This article belongs to the Special Issue Robotics, Automation and Mechatronics (RAM): The Newest Technologies and Applications)
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50 pages, 1909 KiB  
Article
Decoding Digital Synergies: How Mechatronic Systems and Artificial Intelligence Shape Banking Performance Through Quantile-Driven Method of Moments
by Liviu Florin Manta, Alina Georgiana Manta and Claudia Gherțescu
Appl. Sci. 2025, 15(10), 5282; https://doi.org/10.3390/app15105282 - 9 May 2025
Viewed by 343
Abstract
This study investigates the heterogeneous impact of bank automation on institutional performance, emphasizing the role of mechatronic systems like automated teller machines (ATMs) and artificial intelligence-based tools such as chatbots and robo-advisors. Using Method of Moments Quantile Regression (MMQR), the analysis examines how [...] Read more.
This study investigates the heterogeneous impact of bank automation on institutional performance, emphasizing the role of mechatronic systems like automated teller machines (ATMs) and artificial intelligence-based tools such as chatbots and robo-advisors. Using Method of Moments Quantile Regression (MMQR), the analysis examines how these technologies influence key performance indicators, including return on equity (ROE), in the European Union (EU) banking sector from 2017 to 2022. The MMQR method allows for the differentiation of the effects of automation technologies by distinguishing between hardware-based mechatronic systems and software-driven AI solutions, providing a nuanced perspective on the digital transformation within the banking sector. The results highlight the heterogeneous effects of economic, financial, and institutional factors on banking performance in the EU. They emphasize the need for differentiated policy interventions to reduce performance gaps between EU economies and ensure that banks across all member states can leverage financial and technological advancements to enhance profitability. The findings underline the importance of strategic interventions to address digitalization disparities, promote financial inclusion, and establish a regulatory framework that fosters transparency, cybersecurity, and equitable access to AI-driven financial services. Full article
(This article belongs to the Special Issue Robotics, Automation and Mechatronics (RAM): The Newest Technologies and Applications)
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Review

Jump to: Research

35 pages, 1308 KiB  
Review
Review of Fault Detection and Diagnosis Methods in Power Plants: Algorithms, Architectures, and Trends
by Camelia Adela Maican, Cristina Floriana Pană, Daniela Maria Pătrașcu-Pană and Virginia Maria Rădulescu
Appl. Sci. 2025, 15(11), 6334; https://doi.org/10.3390/app15116334 - 5 Jun 2025
Viewed by 380
Abstract
Fault detection and diagnosis (FDD) in power plant systems is a rapidly evolving field driven by the increasing complexity of industrial infrastructure and the demand for reliability, safety, and predictive maintenance. This review presents a structured and data-driven synthesis of 185 peer-reviewed articles, [...] Read more.
Fault detection and diagnosis (FDD) in power plant systems is a rapidly evolving field driven by the increasing complexity of industrial infrastructure and the demand for reliability, safety, and predictive maintenance. This review presents a structured and data-driven synthesis of 185 peer-reviewed articles, sourced from journals indexed in MDPI and Elsevier, as well as through the Google Scholar search engine, published between 2019 and 2025. The study systematically classifies these articles by plant type, sensor technology, algorithm category, and diagnostic pipeline (detection, localization, resolution). The analysis reveals a significant transition from traditional statistical methods to machine learning (ML) and deep learning (DL) models, with over 70% of recent studies employing AI-driven approaches. However, only 30.3% of the articles addressed the full diagnostic pipeline and merely 17.3% targeted system-level faults. Most research remains component-focused and lacks real-world validation or interpretability. A novel taxonomy of diagnostic configurations, mapping system types, sensor use, algorithmic strategy, and functional depth is proposed. In addition, a methodological checklist is introduced to evaluate the completeness and operational readiness of FDD studies. Key findings are summarized in a comparative matrix, highlighting trends, gaps, and inconsistencies across publication sources. This review identifies critical research gaps—including the underuse of hybrid models, lack of benchmark datasets, and limited integration between detection and control layers—and offers concrete recommendations for future research. Combining a thematic and quantitative approach, this article aims to support researchers, engineers, and decision-makers in developing more robust, scalable, and transparent diagnostic systems for power generation infrastructure. Full article
(This article belongs to the Special Issue Robotics, Automation and Mechatronics (RAM): The Newest Technologies and Applications)
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