Autonomous Robotics and Hybrid Intelligent Systems

A special issue of Applied System Innovation (ISSN 2571-5577). This special issue belongs to the section "Control and Systems Engineering".

Deadline for manuscript submissions: 25 February 2026 | Viewed by 1552

Special Issue Editors


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Guest Editor
Department of Computers, Electronics and Automation, Stefan cel Mare University, 720229 Suceava, Romania
Interests: control systems engineering; discrete event systems; metaheuristic systems; electronic engineering
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Guest Editor
Mechanics of Adaptive Systems, Institute for Computational Engineering, Faculty of Civil and Environmental Engineering, Ruhr-Universität Bochum, Universitätsstraße 150, 44801 Bochum, Germany
Interests: advanced control; experimental investigation and implementation
Special Issues, Collections and Topics in MDPI journals

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Guest Editor Assistant
Department of Computer Engineering, International Science and Technology University, National Academy of Sciences of Ukraine, 01030 Kyiv, Ukraine
Interests: AI ecosystem; robotics; machine learning (ML); deep learning (DL)

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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Published Papers (2 papers)

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Research

21 pages, 11514 KB  
Article
Fuzzy Fusion of Monocular ORB-SLAM2 and Tachometer Sensor for Car Odometry
by David Lázaro Mata, José Alfredo Padilla Medina, Juan José Martínez Nolasco, Juan Prado Olivarez and Alejandro Israel Barranco Gutiérrez
Appl. Syst. Innov. 2025, 8(6), 188; https://doi.org/10.3390/asi8060188 - 30 Nov 2025
Viewed by 397
Abstract
Estimating the absolute scale of reconstructed camera trajectories in monocular odometry is a challenging task due to the inherent scale ambiguity in any monocular vision system. One promising solution is to fuse data from different sensors, which can improve the accuracy and precision [...] Read more.
Estimating the absolute scale of reconstructed camera trajectories in monocular odometry is a challenging task due to the inherent scale ambiguity in any monocular vision system. One promising solution is to fuse data from different sensors, which can improve the accuracy and precision of scale estimation. However, this approach often requires additional effort in sensor design and data processing. In this paper, we propose a novel method for fusing single-camera data with wheel odometer readings using a fuzzy system. The architecture of the fuzzy system has as inputs the wheel odometer value and the translation and rotation obtained from ORB-SLAM2. It was trained with the ANFIS tool in MATLAB 2014b. Our approach yields significantly better results compared to state-of-the-art pure monocular systems. In our experiments, the average error relative to GPS measurements was only four percent. A key advantage of this method is the elimination of the sensor calibration step, allowing for straightforward data fusion without a substantial increase in data processing demands. Full article
(This article belongs to the Special Issue Autonomous Robotics and Hybrid Intelligent Systems)
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23 pages, 18423 KB  
Article
Deployable and Habitable Architectural Robot Customized to Individual Behavioral Habits
by Ye Zhang, Penghua Ren, Haoyi Wang, Yu Cui and Zhen Xu
Appl. Syst. Innov. 2025, 8(6), 169; https://doi.org/10.3390/asi8060169 - 5 Nov 2025
Viewed by 852
Abstract
Architectural robotics enables physical spaces and their components to act, think, and grow with their inhabitants. However, this is still a relatively new field that requires further improvements in portability, customizability, and flexibility. This study integrates spatial embedding knowledge, small-space design principles based [...] Read more.
Architectural robotics enables physical spaces and their components to act, think, and grow with their inhabitants. However, this is still a relatively new field that requires further improvements in portability, customizability, and flexibility. This study integrates spatial embedding knowledge, small-space design principles based on human scales and behaviors, and robotic kinematics to propose a prototype robot capable of efficient batch storage, habitability, and autonomous mobility. Based on the spatial distribution of its user’s dynamic skeletal points, determined using a human–computer interaction design system, this prototype robot can automatically adjust parameters to generate a customized solution aligned with the user’s behavioral habits. This study highlights how considering the inhabitant’s personality can create new possibilities for architectural robots and offers insights for future works that expand architecture into intelligent machines. Full article
(This article belongs to the Special Issue Autonomous Robotics and Hybrid Intelligent Systems)
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