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Guo H, Yin H, Song S, Zhu X, Ren D. Application of density clustering with noise combined with particle swarm optimization in UWB indoor positioning. Sci Rep 2024; 14:13121. [PMID: 38849402 PMCID: PMC11161602 DOI: 10.1038/s41598-024-63358-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Accepted: 05/28/2024] [Indexed: 06/09/2024] Open
Abstract
Due to the presence of non-line-of-sight (NLOS) obstacles, the localization accuracy in ultra-wideband (UWB) wireless indoor localization systems is typically substantially lower. To minimize the influence of these environmental factors and improve the accuracy of indoor wireless positioning, this paper proposes a density clustering with noise combined with particle swarm optimization (DCNPSO) to improve UWB positioning. Which exploits the advantages of the density-based spatial clustering algorithm with noise (DBSCAN) and particle swarm optimization (PSO) algorithm. The experimental results show that the DCNPSO algorithm achieves 45.25% and 36.14% higher average positioning accuracy than the DBSCAN and PSO algorithms, respectively. The positioning error of this algorithm remains stable within 3 cm in static positioning and can achieve high accuracy in NLOS environments.
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Affiliation(s)
- Hua Guo
- School of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, 266590, China.
| | - Haozhou Yin
- School of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, 266590, China
| | - Shanshan Song
- School of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, 266590, China
| | - Xiuwei Zhu
- School of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, 266590, China
| | - Daokuan Ren
- School of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, 266590, China
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Rebelo PM, Lima J, Soares SP, Moura Oliveira P, Sobreira H, Costa P. A Performance Comparison between Different Industrial Real-Time Indoor Localization Systems for Mobile Platforms. SENSORS (BASEL, SWITZERLAND) 2024; 24:2095. [PMID: 38610305 PMCID: PMC11014360 DOI: 10.3390/s24072095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 03/11/2024] [Accepted: 03/15/2024] [Indexed: 04/14/2024]
Abstract
The flexibility and versatility associated with autonomous mobile robots (AMR) have facilitated their integration into different types of industries and tasks. However, as the main objective of their implementation on the factory floor is to optimize processes and, consequently, the time associated with them, it is necessary to take into account the environment and congestion to which they are subjected. Localization, on the shop floor and in real time, is an important requirement to optimize the AMRs' trajectory management, thus avoiding livelocks and deadlocks during their movements in partnership with manual forklift operators and logistic trains. Threeof the most commonly used localization techniques in indoor environments (time of flight, angle of arrival, and time difference of arrival), as well as two of the most commonly used indoor localization methods in the industry (ultra-wideband, and ultrasound), are presented and compared in this paper. Furthermore, it identifies and compares three industrial indoor localization solutions: Qorvo, Eliko Kio, and Marvelmind, implemented in an industrial mobile platform, which is the main contribution of this paper. These solutions can be applied to both AMRs and other mobile platforms, such as forklifts and logistic trains. In terms of results, the Marvelmind system, which uses an ultrasound method, was the best solution.
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Affiliation(s)
- Paulo M. Rebelo
- Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), 4200-465 Porto, Portugal; (J.L.); (P.M.O.); (H.S.); (P.C.)
- School of Sciences and Technology-Engineering Department (UTAD), 5000-801 Vila Real, Portugal;
| | - José Lima
- Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), 4200-465 Porto, Portugal; (J.L.); (P.M.O.); (H.S.); (P.C.)
- CeDRI, SusTEC, Instituto Politécnico de Bragança, Campus Sta Apolónia, 5300-253 Bragança, Portugal
| | - Salviano Pinto Soares
- School of Sciences and Technology-Engineering Department (UTAD), 5000-801 Vila Real, Portugal;
- Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, 3810-193 Aveiro, Portugal
- Intelligent Systems Associate Laboratory (LASI), University of Minho, 4800-058 Guimarães, Portugal
| | - Paulo Moura Oliveira
- Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), 4200-465 Porto, Portugal; (J.L.); (P.M.O.); (H.S.); (P.C.)
- School of Sciences and Technology-Engineering Department (UTAD), 5000-801 Vila Real, Portugal;
| | - Héber Sobreira
- Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), 4200-465 Porto, Portugal; (J.L.); (P.M.O.); (H.S.); (P.C.)
| | - Pedro Costa
- Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), 4200-465 Porto, Portugal; (J.L.); (P.M.O.); (H.S.); (P.C.)
- Faculty of Engineering, University of Porto (FEUP), 4200-465 Porto, Portugal
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Ciężkowski M, Kociszewski R. Fast 50 Hz Updated Static Infrared Positioning System Based on Triangulation Method. SENSORS (BASEL, SWITZERLAND) 2024; 24:1389. [PMID: 38474925 DOI: 10.3390/s24051389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 02/16/2024] [Accepted: 02/19/2024] [Indexed: 03/14/2024]
Abstract
One of the important issues being explored in Industry 4.0 is collaborative mobile robots. This collaboration requires precise navigation systems, especially indoor navigation systems where GNSS (Global Navigation Satellite System) cannot be used. To enable the precise localization of robots, different variations of navigation systems are being developed, mainly based on trilateration and triangulation methods. Triangulation systems are distinguished by the fact that they allow for the precise determination of an object's orientation, which is important for mobile robots. An important feature of positioning systems is the frequency of position updates based on measurements. For most systems, it is 10-20 Hz. In our work, we propose a high-speed 50 Hz positioning system based on the triangulation method with infrared transmitters and receivers. In addition, our system is completely static, i.e., it has no moving/rotating measurement sensors, which makes it more resistant to disturbances (caused by vibrations, wear and tear of components, etc.). In this paper, we describe the principle of the system as well as its design. Finally, we present tests of the built system, which show a beacon bearing accuracy of Δφ = 0.51°, which corresponds to a positioning accuracy of ΔR = 6.55 cm, with a position update frequency of fupdate = 50 Hz.
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Affiliation(s)
- Maciej Ciężkowski
- Automatic Control and Robotics Department, Faculty of Electrical Engineering, Bialystok University of Technology, Wiejska St. 45D, 15-351 Bialystok, Poland
| | - Rafał Kociszewski
- Automatic Control and Robotics Department, Faculty of Electrical Engineering, Bialystok University of Technology, Wiejska St. 45D, 15-351 Bialystok, Poland
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Wu M, Li Z, Chen J, Min Q, Lu T. A Dual Cluster-Head Energy-Efficient Routing Algorithm Based on Canopy Optimization and K-Means for WSN. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22249731. [PMID: 36560099 PMCID: PMC9784440 DOI: 10.3390/s22249731] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 11/24/2022] [Accepted: 12/07/2022] [Indexed: 06/12/2023]
Abstract
Wireless sensor networks (WSN) are widely used in various applications, such as environmental monitoring, healthcare, event detection, agriculture, disaster management, and so on. Due to their small size, sensors are limited power sources and are often deployed in special environments where frequent battery replacement is not feasible. Therefore, it is important to reduce the energy consumption of sensors and extend the network lifetime. An effective way to achieve this is clustering. This paper proposes a dual cluster-head energy-efficient algorithm (DCK-LEACH), which is based on K-means and Canopy optimization. Considering that the K-means algorithm is sensitive to the location of the initial clustering centers, this paper uses both the dynamic Canopy algorithm and K-means algorithm for clustering. For cluster-head election, this algorithm uses a hierarchy to minimize the cluster-head burden and balance the network load. The primary cluster-head is selected by two objectives: the node's residual energy and the distance from the node to the clustering center. The vice cluster-head is selected by the residual energy of the node, and the distance from the nodes to the base station. Simulator results show that DCK-LEACH significantly prolongs the energy-critical node lifetime and the network lifetime compared with existing protocols.
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Affiliation(s)
- Mei Wu
- School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, China
| | - Zhengliang Li
- School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, China
| | - Jing Chen
- School of Mathematics and Physics, Wuhan Institute of Technology, Wuhan 430205, China
| | - Qiusha Min
- School of Educational Information Technology, Central China Normal University, Wuhan 430079, China
| | - Tao Lu
- School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, China
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