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Sensing and AI: Advancements in Robotics and Autonomous Systems

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

Deadline for manuscript submissions: 28 February 2026 | Viewed by 199

Special Issue Editors


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Guest Editor
Department of Mechanical and Aerospace Engineering, Brunel University, London UB8 3PH, UK
Interests: force and tactile sensors; haptics; robot assisted ultrasound diagnostic system; medical training system; medical robots; robot platform software development; flexible manipulators; shape sensors; surgical robots; soft manipulators

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Guest Editor
Department of Electronic and Electrical Engineering, Brunel University London, Kingston Ln, Uxbridge UB8 3PH, UK
Interests: robotics; control systems; mobile robot; capsule robot; capsule endoscopy; artificial intelligence; deep learning; sensor fusion; robotic (self-driving) cars; robotics and AI for healthcare
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Mechanical and Aerospace Engineering, Brunel University London, London UB8 3PH, UK
Interests: continuum robotic systems for in-situ maintenance; legged robotic systems with parallel mechanisms; soft robotic systems with embedded sensing; precision farming robotic systems; miniaturised robotic systems

Special Issue Information

Dear Colleagues,

Recent advancements in sensing technology and artificial intelligence (AI) have revolutionised mechanism design, paving the way for groundbreaking developments in robotics and automation. The integration of high-precision sensors with AI-driven algorithms has enabled more adaptive, efficient, and intelligent robotic systems, transforming industries ranging from manufacturing and healthcare to space exploration and autonomous vehicles.

This special issue focuses on the latest innovations and applications at the intersection of sensing technology, AI, and mechanism design. Topics of interest include novel sensing techniques, AI-enhanced control systems, machine learning for optimisation, bio-inspired robotics, and real-time data processing for automation. By bringing together cutting-edge research and practical applications, this issue aims to highlight emerging trends, address key challenges, and foster collaboration among researchers, engineers, and industry professionals.

We invite contributions that explore theoretical frameworks, experimental studies, and real-world implementations, offering insights into the next generation of robotic and autonomous systems.

Dr. Yohan Noh
Dr. Md Nazmul Huda
Dr. Mingfeng Wang
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 technology
  • Artificial Intelligence (AI)
  • mechanism design
  • robotics automation
  • smart sensors
  • machine learning
  • control systems
  • bio-inspired robotics
  • human-robot interaction
  • autonomous systems
  • industrial automation
  • deep learning in robotics
  • embedded AI
  • tactile and vision-based sensing

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Published Papers (1 paper)

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Research

21 pages, 33901 KiB  
Article
Scalable, Flexible, and Affordable Hybrid IoT-Based Ambient Monitoring Sensor Node with UWB-Based Localization
by Mohammed Faeik Ruzaij Al-Okby, Thomas Roddelkopf, Jiahao Huang, Mohsin Bukhari and Kerstin Thurow
Sensors 2025, 25(13), 4061; https://doi.org/10.3390/s25134061 (registering DOI) - 29 Jun 2025
Abstract
Ambient monitoring in chemical laboratories and industrial sites that use toxic, hazardous, or flammable materials is essential to protect the lives of workers, material resources, and infrastructure at these sites. In this research paper, we present an innovative approach for developing a low-cost [...] Read more.
Ambient monitoring in chemical laboratories and industrial sites that use toxic, hazardous, or flammable materials is essential to protect the lives of workers, material resources, and infrastructure at these sites. In this research paper, we present an innovative approach for developing a low-cost and portable sensor node that detects and warns of hazardous chemical gas and vapor leaks. The system also enables leak location tracking using an indoor tracking and positioning system operating in ultra-wideband (UWB) technology. An array of sensors is used to detect gases, vapors, and airborne particles, while the leak location is identified through a UWB unit integrated with an Internet of Things (IoT) processor. This processor transmits real-time location data and sensor readings via wireless fidelity (Wi-Fi). The real-time indoor positioning system (IPS) can automatically select a tracking area based on the distances measured from the three nearest anchors of the movable sensor node. The environmental sensor data and distances between the node and the anchors are transmitted to the cloud in JSON format via the user datagram protocol (UDP), which allows the fastest possible data rate. A monitoring server was developed in Python to track the movement of the portable sensor node and display live measurements of the environment. The system was tested by selecting different paths between several adjacent areas with a chemical leakage of different volatile organic compounds (VOCs) in the test path. The experimental tests demonstrated good accuracy in both hazardous gas detection and location tracking. The system successfully issued a leak warning for all tested material samples with volumes up to 500 microliters and achieved a positional accuracy of approximately 50 cm under conditions without major obstacles obstructing the UWB signal between the active system units. Full article
(This article belongs to the Special Issue Sensing and AI: Advancements in Robotics and Autonomous Systems)
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