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Mobile Robots: Navigation, Control and Sensing—2nd Edition
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Mobile Robots: Navigation, Control and Sensing—2nd Edition

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

Deadline for manuscript submissions: 31 March 2025 | Viewed by 2833

Special Issue Editors

Dr. David Cheneler

E-Mail Website
Guest Editor
Department of Engineering, Lancaster University, Lancaster LA1 4YW, UK
Interests: sensors; nuclear instrumentation; sub-aquatic robotics
Special Issues, Collections and Topics in MDPI journals
Dr. Stephen Monk

E-Mail Website
Guest Editor
Department of Engineering, Lancaster University, Lancaster LA1 4YW, UK
Interests: radiological instrumentation; robotics in nuclear decommissioning environments
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Navigation is one of the main challenges faced in robotics. Different technologies and strategies are involved, such as sensing, positioning, mapping, approaching, tracking, formation, control, communication, human interface, learning, etc.

The aim of this Special Issue is to contribute state-of-the-art research and present current applications of robot navigation. The Guest Editors invite papers related to the following topics, but the list is non-exhaustive, as follows:

  1. Development of robotics and sensors designed to be utilized within any radiological environment.
  2. Perception and stand-alone and cooperative approaches; SLAM.
  3. Map-based, landmark-based, and beacon-based navigation (2D and 3D).
  4. Data fusion for mobile robot navigation.
  5. Wireless sensor networks for mobile robot navigation.
  6. Network control systems.
  7. Robot formation and tracking.
  8. Adaptive robot navigation and control.
  9. Biologically inspired robot navigation.
  10. Path planning.
  11. Applications of mobile robot navigation.
  12. Genetic algorithm for mobile robot navigation.
  13. Tracking algorithms.

Dr. David Cheneler
Dr. Stephen Monk
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

  • mobile robot
  • path planning
  • navigation
  • positioning
  • mapping

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Published Papers (3 papers)

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Research

39 pages, 23368 KiB  
Article
Vision-Based Localization in Urban Areas for Mobile Robots
by Erdal Alimovski, Gokhan Erdemir and Ahmet Emin Kuzucuoglu
Sensors 2025, 25(4), 1178; https://doi.org/10.3390/s25041178 - 14 Feb 2025
Viewed by 340
Abstract
Robust autonomous navigation systems rely on mapping, locomotion, path planning, and localization factors. Localization, one of the most essential factors of navigation, is a crucial requirement for a mobile robot because it needs the capability to localize itself in the environment. Global Positioning [...] Read more.
Robust autonomous navigation systems rely on mapping, locomotion, path planning, and localization factors. Localization, one of the most essential factors of navigation, is a crucial requirement for a mobile robot because it needs the capability to localize itself in the environment. Global Positioning Systems (GPSs) are commonly used for outdoor mobile robot localization tasks. However, various environmental circumstances, such as high-rise buildings and trees, affect GPS signal quality, which leads to reduced precision or complete signal blockage. This study proposes a visual-based localization system for outdoor mobile robots in crowded urban environments. The proposed system comprises three steps. The first step is to detect the text in urban areas using the “Efficient and Accurate Scene Text Detector (EAST)” algorithm. Then, EasyOCR was applied to the detected text for the recognition phase to extract text from images that were obtained from EAST. The results from text detection and recognition algorithms were enhanced by applying post-processing and word similarity algorithms. In the second step, once the text detection and recognition process is completed, the recognized word (label/tag) is sent to the Places API in order to return the recognized word’s coordinates that are passed within the specified radius. Parallely, points of interest (POI) data are collected for a defined area by a certain radius while the robot has an accurate internet connection. The proposed system was tested in three distinct urban areas by creating five scenarios under different lighting conditions, such as morning and evening, using the outdoor delivery robot utilized in this study. In the case studies, it has been shown that the proposed system provides a low error of around 4 m for localization tasks. Compared to existing works, the proposed system consistently outperforms all other approaches using just one sensor. The results indicate the efficacy of the proposed system for localization tasks in environments where GPS signals are limited or completely blocked. Full article
(This article belongs to the Special Issue Mobile Robots: Navigation, Control and Sensing—2nd Edition)
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18 pages, 46192 KiB  
Article
Design Analysis and Isotropic Optimization for Miniature Capacitive Force/Torque Sensor
by Seung Yeon Lee, Jae Yoon Sim, Yong Bum Kim, Dongyeop Seok, Jaeyoon Shim and Hyouk Ryeol Choi
Sensors 2025, 25(3), 940; https://doi.org/10.3390/s25030940 - 4 Feb 2025
Viewed by 652
Abstract
A capacitive six-axis force/torque (F/T) sensor has favorable characteristics for miniature design. However, when designing small-sized force/torque sensors, anisotropy among the six axes can lead to uneven sensitivity across each axis. This is due to increased crosstalk errors, which degrade sensor performance. To [...] Read more.
A capacitive six-axis force/torque (F/T) sensor has favorable characteristics for miniature design. However, when designing small-sized force/torque sensors, anisotropy among the six axes can lead to uneven sensitivity across each axis. This is due to increased crosstalk errors, which degrade sensor performance. To design a miniature six-axis force/torque sensor, it is essential to analyze the isotropic relationships between the six-axis forces/torques and the capacitance change to reduce crosstalk errors. This paper presents a miniature capacitive six-axis F/T sensor optimized for isotropy. It also establishes a systematic method for designing sensing electrodes. The sensor’s deformable structure is analyzed using Castigliano’s beam theory, and design parameters are optimized with isotropy analysis of the deformable part. The criteria are also presented, including selecting the electrode area and initial gap using linear equations derived from capacitance change analysis. The optimized miniature F/T sensor is calibrated using a neural network-based calibration method, and its accuracy errors are compared to a reference sensor. The design framework provides a foundation for future developments in miniature sensors. Full article
(This article belongs to the Special Issue Mobile Robots: Navigation, Control and Sensing—2nd Edition)
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16 pages, 4643 KiB  
Article
A Retrospective Analysis of Indoor CO2 Measurements Obtained with a Mobile Robot during the COVID-19 Pandemic
by Jordi Palacín, Elena Rubies and Eduard Clotet
Sensors 2024, 24(10), 3102; https://doi.org/10.3390/s24103102 - 13 May 2024
Cited by 1 | Viewed by 1330
Abstract
This work presents a retrospective analysis of indoor CO2 measurements obtained with a mobile robot in an educational building after the COVID-19 lockdown (May 2021), at a time when public activities resumed with mandatory local pandemic restrictions. The robot-based CO2 measurement [...] Read more.
This work presents a retrospective analysis of indoor CO2 measurements obtained with a mobile robot in an educational building after the COVID-19 lockdown (May 2021), at a time when public activities resumed with mandatory local pandemic restrictions. The robot-based CO2 measurement system was assessed as an alternative to the deployment of a net of sensors in a building in the pandemic period, in which there was a global stock outage of CO2 sensors. The analysis of the obtained measurements confirms that a mobile system can be used to obtain interpretable information on the CO2 levels inside the rooms of a building during a pandemic outbreak. Full article
(This article belongs to the Special Issue Mobile Robots: Navigation, Control and Sensing—2nd Edition)
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