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Sensing for Automatic Control and Measurement System
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Sensing for Automatic Control and Measurement System

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

Deadline for manuscript submissions: 10 November 2025 | Viewed by 2893

Special Issue Editors

Prof. Dr. Igor Korobiichuk

E-Mail Website
Guest Editor
Institute of Automatic Control and Robotics, Warsaw University of Technology, 02-525 Warsaw, Poland
Interests: measurement systems; control and instrumentation; inertial navigation systems; mechatronics
Special Issues, Collections and Topics in MDPI journals
Dr. Michał Nowicki

E-Mail Website
Guest Editor
Institute of Metrology and Biomedical Engineering, Warsaw University of Technology, A. Boboli 8, 02-525 Warsaw, Poland
Interests: advanced measuring techniques for smart materials, especially for the robotic applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The objective of this Special Issue is to bring together researchers, scientists, and engineers from academia and industry to share their latest findings, innovations, and experiences in the domain of sensing for automatic control and measurement systems. By highlighting recent developments, emerging trends, and challenges, we aim to foster a deeper understanding of the critical role sensors play in enabling accurate and efficient control and measurement processes.

Scope and Topics:

Contributions to this Special Issue will cover a wide range of topics related to sensing technologies, automatic control, and measurement systems. Potential areas of interest include, but are not limited to, the following:

  • Sensing techniques for control and measurement systems;
  • Sensor fusion and integration for enhanced system performance;
  • Intelligent sensing systems for automation and optimization;
  • Signal processing and data analysis for sensor-based control systems;
  • Novel sensors and transducers for improved system performance;
  • Sensing technologies for industrial automation and process control;
  • Sensing for smart grid and energy management systems;
  • Sensing for robotics and autonomous systems.

Prof. Dr. Igor Korobiichuk
Dr. Michał Nowicki
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. 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

  • sensing technologies
  • automatic control
  • measurement systems
  • autonomous systems
  • sensor-based control
  • calibration techniques
  • process control

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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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34 pages, 2272 KiB  
Article
Intelligent Fault-Tolerant Control of Delta Robots: A Hybrid Optimization Approach for Enhanced Trajectory Tracking
by Carlos Domínguez and Claudio Urrea
Sensors 2025, 25(6), 1940; https://doi.org/10.3390/s25061940 - 20 Mar 2025
Viewed by 358
Abstract
The kinematic complexity and multi-actuator dependence of Delta-type manipulators render them vulnerable to performance degradation from faults. This study presents a novel approach to Active Fault-Tolerant Control (AFTC) for Delta-type parallel robots, integrating an advanced fault diagnosis system with a robust control strategy. [...] Read more.
The kinematic complexity and multi-actuator dependence of Delta-type manipulators render them vulnerable to performance degradation from faults. This study presents a novel approach to Active Fault-Tolerant Control (AFTC) for Delta-type parallel robots, integrating an advanced fault diagnosis system with a robust control strategy. In the first stage, a fault diagnosis system is developed, leveraging a hybrid feature extraction algorithm that combines Wavelet Scattering Networks (WSNs), Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Meta-Learning (ML). This system effectively identifies and classifies faults affecting single actuators, sensors, and multiple components under real-time conditions. The proposed AFTC approach employs a hybrid optimization framework that integrates Genetic Algorithms and Gradient Descent to reconfigure a Type-2 fuzzy controller. Results show that the methodology achieves perfect fault diagnosis accuracy across four classifiers and enhances robot performance by reducing critical degradation to moderate levels under multiple faults. These findings validate the robustness and efficiency of the proposed fault-tolerant control strategy, highlighting its potential for enhancing trajectory tracking accuracy in complex robotic systems under adverse conditions. Full article
(This article belongs to the Special Issue Sensing for Automatic Control and Measurement System)
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Review

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25 pages, 1454 KiB  
Review
Hybrid Mode Sensor Fusion for Accurate Robot Positioning
by Viktor Masalskyi, Andrius Dzedzickis, Igor Korobiichuk and Vytautas Bučinskas
Sensors 2025, 25(10), 3008; https://doi.org/10.3390/s25103008 - 10 May 2025
Viewed by 236
Abstract
Robotic systems are becoming increasingly crucial in applications requiring high precision. While a robot can operate using basic sensor feedback under controlled conditions, achieving micro-level accuracy requires more comprehensive data integration, especially in dynamic environments. The fusion of data from a variety of [...] Read more.
Robotic systems are becoming increasingly crucial in applications requiring high precision. While a robot can operate using basic sensor feedback under controlled conditions, achieving micro-level accuracy requires more comprehensive data integration, especially in dynamic environments. The fusion of data from a variety of sensors is necessary for improving the positioning accuracy of a robot because the accuracy of one type of sensor is insufficient. The field of micro-positioning presents new challenges and tasks that have been gradually explored in the recent literature published from 2015 to 2025. Micro-positioning is a complex operation that involves factors such as mechanical drift, environmental effects, and sensor signal errors. Hybrid fusion is a sensor fusion technique that combines elements of fusion at different levels. For the effective deployment of robots in such contexts, it is essential to integrate multiple sensors and ensure reliable data fusion between them. This involves the use of different sensors, advanced fusion algorithms, and accurate calibration methods through sensor fusion and sophisticated data processing techniques. This literature review presents an analysis of the sensor data fusion methods for precise robot micro-positioning. The focus is on the investigated sensors, the applied synthesis methods, and the developed algorithms and their practical application to identify the existing gaps for future system improvements. Finally, discussions and conclusions based on the collected ideas are presented. Full article
(This article belongs to the Special Issue Sensing for Automatic Control and Measurement System)
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27 pages, 1452 KiB  
Review
A Review of Multi-Robot Systems and Soft Robotics: Challenges and Opportunities
by Juan C. Tejada, Alejandro Toro-Ossaba, Alexandro López-Gonzalez, Eduardo G. Hernandez-Martinez and Daniel Sanin-Villa
Sensors 2025, 25(5), 1353; https://doi.org/10.3390/s25051353 - 22 Feb 2025
Viewed by 1851
Abstract
This review investigates the latest advancements in Multi-Robot Systems (MRSs) and soft robotics, with a particular focus on their integration and emerging opportunities. An MRS extends principles from distributed artificial intelligence and coordination frameworks, enabling efficient collaboration in robotic applications such as object [...] Read more.
This review investigates the latest advancements in Multi-Robot Systems (MRSs) and soft robotics, with a particular focus on their integration and emerging opportunities. An MRS extends principles from distributed artificial intelligence and coordination frameworks, enabling efficient collaboration in robotic applications such as object manipulation, navigation, and transportation. Soft robotics employs flexible materials and biomimetic designs to improve adaptability in unstructured environments, with applications in manufacturing, sensing, actuation, and modeling. Unlike previous reviews, which often address these fields independently, this work emphasizes their integration, identifying key challenges such as nonlinear dynamics, hyper-redundant configurations, and adaptive control. This review discusses recent advancements in locomotion, coordination, and simulation, offering insights into the development of adaptive and collaborative robotic systems across diverse applications. Full article
(This article belongs to the Special Issue Sensing for Automatic Control and Measurement System)
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