Localization Technologies

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 5301

Special Issue Editors


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Guest Editor
Department of Communications Engineering, University of Málaga, 29071 Málaga, Spain
Interests: cellular networks; wireless industrial communications; machine learning; IoT; big data analytics; wireless network testbeds; wireless network simulation; robotics
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Guest Editor
Center for Wireless Communications (CWC), University of Oulu, 90014 Oulu, Finland
Interests: beyond 5G/6G wireless systems; industrial IoT; machine type communications; URLLC
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Samsung UK, London TW18 4QE, UK
Interests: 5G-NR based localization; UWB localization and ranging; 3GPP NTN standardization; drone based Ad-hoc communication; mission critical communications
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Centre for Wireless Communications/6G Flagship, Department of Communications and Engineering, University of Oulu, Oulu, Finland
Interests: 5G and B5G communication systems; localization and Sensing; cyber-physical systems; information fusion and analytics; statistical signal processing; probabilistic programming.

Special Issue Information

Dear Colleagues,

Portable computing and portable communications are rapidly becoming the norm in the market of electronic systems. As a consequence of this, an ecosystem of applications that are somehow linked to location is growing, both in the market and in academia. A broad range of vertical sectors benefit from these applications, such as the manufacturing industry, Smart Cities, travel services or autonomous vehicles. At the core of these applications resides a set of technologies that exploit diverse resources in order to provide a reliable location. However, providing location is not a trivial problem, nor does it come at a low cost. Therefore, location is currently a hot topic in the research community. It is also a very broad topic, both in use cases and technologies that are exploited to provide location: satellite-based systems, wireless network location, sensors, video-based location (which is often intertwined with object recognition), etc. This Special Issue aims at providing a multi-disciplinary picture of the current state of location technologies. Contributions that describe and characterize novel use cases for location technologies, analyze current and emerging technologies, propose improvements on already existing solutions with techniques, such as Machine Learning and Artificial Intelligence, or that propose radical new approaches, based on novel devices, are welcome.

Dr. Emil J. Khatib
Dr. Nurul Huda Mahmood
Dr. Mythri Hunukumbure
Dr. Carlos Morais de Lima
Guest Editors

Manuscript Submission Information

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Keywords

  • Location technologies, Location awareness
  • Location tracking
  • Wireless networks
  • Artificial Intelligence

Published Papers (2 papers)

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Research

21 pages, 4941 KiB  
Article
Performance Evaluation of a UWB Positioning System Applied to Static and Mobile Use Cases in Industrial Scenarios
by Allan Schjørring, Amalia Lelia Cretu-Sircu, Ignacio Rodriguez, Peter Cederholm, Gilberto Berardinelli and Preben Mogensen
Electronics 2022, 11(20), 3294; https://doi.org/10.3390/electronics11203294 - 13 Oct 2022
Cited by 7 | Viewed by 1936
Abstract
Indoor positioning systems are essential in the industrial domain for optimized production and safe operation of mobile elements, such as mobile robots, especially in the presence of static machinery and human operators. In this paper, we assess the performance of a commercial UWB [...] Read more.
Indoor positioning systems are essential in the industrial domain for optimized production and safe operation of mobile elements, such as mobile robots, especially in the presence of static machinery and human operators. In this paper, we assess the performance of a commercial UWB radio-based positioning system deployed in a realistic industrial scenario, considering both static and mobile use cases. Our goal is to characterize the accuracy of this system in the context of industrial use cases and applications. For the static case, an extensive analysis was presented based on measurements performed at 72 measurement positions at 3 different heights (above, at similar a level to, and below the average clutter level) in different industrial clutter conditions (open and cluttered spaces). The extensive analysis in the mobile case considered several runs of a route covered by an autonomous mobile robot equipped with multiple tags in different positions. The results indicate that a similar degree of accuracy with a median 2D positioning error smaller than 20 cm is possible in both static and mobile conditions with an optimized anchor deployment. The paper provides a complete statistical characterization of the system’s accuracy and addresses the multiple deployment trade-offs and system dynamics observed for the different configurations. Full article
(This article belongs to the Special Issue Localization Technologies)
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15 pages, 2712 KiB  
Article
An Improved Initialization Method for Monocular Visual-Inertial SLAM
by Jun Cheng, Liyan Zhang and Qihong Chen
Electronics 2021, 10(24), 3063; https://doi.org/10.3390/electronics10243063 - 9 Dec 2021
Cited by 11 | Viewed by 2469
Abstract
In the aim of improving the positioning accuracy of the monocular visual-inertial simultaneous localization and mapping (VI-SLAM) system, an improved initialization method with faster convergence is proposed. This approach is classified into three parts: Firstly, in the initial stage, the pure vision measurement [...] Read more.
In the aim of improving the positioning accuracy of the monocular visual-inertial simultaneous localization and mapping (VI-SLAM) system, an improved initialization method with faster convergence is proposed. This approach is classified into three parts: Firstly, in the initial stage, the pure vision measurement model of ORB-SLAM is employed to make all the variables visible. Secondly, the frequency of the IMU and camera was aligned by IMU pre-integration technology. Thirdly, an improved iterative method is put forward for estimating the initial parameters of IMU faster. The estimation of IMU initial parameters is divided into several simpler sub-problems, containing direction refinement gravity estimation, gyroscope deviation estimation, accelerometer bias, and scale estimation. The experimental results on the self-built robot platform show that our method can up-regulate the initialization convergence speed, simultaneously improve the positioning accuracy of the entire VI-SLAM system. Full article
(This article belongs to the Special Issue Localization Technologies)
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