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Autonomous Robotics and Hybrid Intelligent Systems
This special issue belongs to the section “Control and Systems Engineering“.
Special Issue Information
Dear Colleagues,
The rapid convergence of autonomous robotics and hybrid intelligent systems is reshaping the boundaries of machine intelligence and its interaction with the physical world. In the face of increasingly complex environments and demanding applications, the need for systems that can seamlessly integrate autonomy, adaptability, and intelligence has never been more critical. This Special Issue, entitled “Autonomous Robotics and Hybrid Intelligent Systems”, aims to address this urgent demand with academic rigor, interdisciplinary depth, and forward-thinking insight.
This Special Issue offers a comprehensive exploration of how modern robotics is evolving beyond traditional control paradigms to embrace the synergistic capabilities of hybrid intelligent approaches, merging symbolic reasoning, machine learning, fuzzy logic, neural computation, and evolutionary algorithms. The result is a compelling narrative that captures the state of the art and anticipates the future trajectory of intelligent autonomous agents capable of operating with resilience and purpose in real-world settings.
What distinguishes this work is its dual focus on the theoretical underpinnings of autonomy and hybrid intelligence and on the practical implementations that bring these concepts to life in robotic platforms. From foundational models and architectures to emerging applications in search and rescue, environmental monitoring, and human–robot collaboration, this Special Issue aims to collectively map the intellectual terrain of this rapidly developing field.
The academic audience—including researchers, graduate students, and advanced practitioners—will find a rich source of knowledge, critical analysis, and inspiration in this Special Issue. Each contribution will be meticulously curated to reflect current challenges and opportunities, fostering a deeper understanding of how hybrid intelligent systems can enhance robotic autonomy in dynamic, uncertain, and unstructured environments.
As robotics continues to transition from isolated automation to collaborative, context-aware systems, this Special Issue stands as a timely and essential resource. It not only charts the progress achieved thus far but also sets the stage for the innovations yet to come.
Dr. Calin Ciufudean
Prof. Dr. Tamara Nestorović
Guest Editors
Dr. Olena Hrybiuk
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 250 words) can be sent to the Editorial Office for assessment.
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 System Innovation 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 1600 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
- autonomous robotics
- artificial intelligence in robotics
- intelligent control systems
- machine learning for robotics
- fuzzy logic controllers
- neural networks
- evolutionary computation
- swarm intelligence
- path planning and navigation
- human–robot interaction
- multi-agent systems
- service robotics
- industrial automation
- robotics in healthcare
- AI for cyber–physical systems
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