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Guo P, Luo D, Wu Y, He S, Deng J, Yao H, Sun W, Zhang J. Coverage Planning for UVC Irradiation: Robot Surface Disinfection Based on Swarm Intelligence Algorithm. SENSORS (BASEL, SWITZERLAND) 2024; 24:3418. [PMID: 38894209 PMCID: PMC11174843 DOI: 10.3390/s24113418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 05/16/2024] [Accepted: 05/22/2024] [Indexed: 06/21/2024]
Abstract
Ultraviolet (UV) radiation has been widely utilized as a disinfection strategy to effectively eliminate various pathogens. The disinfection task achieves complete coverage of object surfaces by planning the motion trajectory of autonomous mobile robots and the UVC irradiation strategy. This introduces an additional layer of complexity to path planning, as every point on the surface of the object must receive a certain dose of irradiation. Nevertheless, the considerable dosage required for virus inactivation often leads to substantial energy consumption and dose redundancy in disinfection tasks, presenting challenges for the implementation of robots in large-scale environments. Optimizing energy consumption of light sources has become a primary concern in disinfection planning, particularly in large-scale settings. Addressing the inefficiencies associated with dosage redundancy, this study proposes a dose coverage planning framework, utilizing MOPSO to solve the multi-objective optimization model for planning UVC dose coverage. Diverging from conventional path planning methodologies, our approach prioritizes the intrinsic characteristics of dose accumulation, integrating a UVC light efficiency factor to mitigate dose redundancy with the aim of reducing energy expenditure and enhancing the efficiency of robotic disinfection. Empirical trials conducted with autonomous disinfecting robots in real-world settings have corroborated the efficacy of this model in deactivating viruses.
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Affiliation(s)
- Peiyao Guo
- Research Center for Optoelectronic Materials and Devices, Guangxi Key Laboratory for the Relativistic Astrophysics, School of Physical Science & Technology, Guangxi University, Nanning 530004, China; (P.G.); (D.L.); (Y.W.); (S.H.); (J.D.)
| | - Dekun Luo
- Research Center for Optoelectronic Materials and Devices, Guangxi Key Laboratory for the Relativistic Astrophysics, School of Physical Science & Technology, Guangxi University, Nanning 530004, China; (P.G.); (D.L.); (Y.W.); (S.H.); (J.D.)
| | - Yizhen Wu
- Research Center for Optoelectronic Materials and Devices, Guangxi Key Laboratory for the Relativistic Astrophysics, School of Physical Science & Technology, Guangxi University, Nanning 530004, China; (P.G.); (D.L.); (Y.W.); (S.H.); (J.D.)
| | - Sheng He
- Research Center for Optoelectronic Materials and Devices, Guangxi Key Laboratory for the Relativistic Astrophysics, School of Physical Science & Technology, Guangxi University, Nanning 530004, China; (P.G.); (D.L.); (Y.W.); (S.H.); (J.D.)
| | - Jianyu Deng
- Research Center for Optoelectronic Materials and Devices, Guangxi Key Laboratory for the Relativistic Astrophysics, School of Physical Science & Technology, Guangxi University, Nanning 530004, China; (P.G.); (D.L.); (Y.W.); (S.H.); (J.D.)
| | - Huilu Yao
- School of Electrical Engineering, Guangxi University, Nanning 530004, China;
| | - Wenhong Sun
- Research Center for Optoelectronic Materials and Devices, Guangxi Key Laboratory for the Relativistic Astrophysics, School of Physical Science & Technology, Guangxi University, Nanning 530004, China; (P.G.); (D.L.); (Y.W.); (S.H.); (J.D.)
- MOE Key Laboratory of New Processing Technology for Nonferrous Metals and Materials, Guangxi Key Laboratory of Processing for Non-Ferrous Metals and Featured Materials, Nanning 530004, China
- Third Generation Semiconductor Industry Research Institute, Guangxi University, Nanning 530004, China
| | - Jicai Zhang
- College of Mathematics and Physics, Beijing University of Chemical Technology, Beijing 100029, China;
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Huang SP, Chen CB, Wei TZ, Tsai WT, Liou CY, Mao YM, Sheng WH, Mao SG. Range-Extension Algorithms and Strategies for TDOA Ultra-Wideband Positioning System. SENSORS (BASEL, SWITZERLAND) 2023; 23:3088. [PMID: 36991800 PMCID: PMC10053965 DOI: 10.3390/s23063088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 03/07/2023] [Accepted: 03/07/2023] [Indexed: 06/19/2023]
Abstract
The Internet of Things (IoT) for smart industry requires the surveillance and management of people and objects. The ultra-wideband positioning system is an attractive solution for achieving centimeter-level accuracy in target location. While many studies have focused on improving the accuracy of the anchor coverage range, it is important to note that in practical applications, positioning areas are often limited and obstructed by furniture, shelves, pillars, or walls, which can restrict the placement of anchors. Furthermore, some positioning regions are located beyond anchor coverage, and a single group with few anchors may not be able to cover all rooms and aisles on a floor due to non-line-of-sight errors causing severe positioning errors. In this work, we propose a dynamic-reference anchor time difference of arrival (TDOA) compensation algorithm to enhance accuracy beyond anchor coverage by eliminating local minima of the TDOA loss function near anchors. We designed a multidimensional and multigroup TDOA positioning system with the aim of broadening the coverage of indoor positioning and accommodating complex indoor environments. By employing an address-filter technique and group-switching process, tags can seamlessly move between groups with a high positioning rate, low latency, and high accuracy. We deployed the system in a medical center to locate and manage researchers with infectious medical waste, demonstrating its usefulness for practical healthcare institutions. Our proposed positioning system can thus facilitate precise and wide-range indoor and outdoor wireless localization.
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Affiliation(s)
- Shih-Ping Huang
- Graduate Institute of Commutation Engineering, National Taiwan University, Taipei 106, Taiwan
| | - Chien-Bang Chen
- Graduate Institute of Commutation Engineering, National Taiwan University, Taipei 106, Taiwan
| | - Tan-Zhi Wei
- Graduate Institute of Commutation Engineering, National Taiwan University, Taipei 106, Taiwan
| | - Wei-Ting Tsai
- Graduate Institute of Commutation Engineering, National Taiwan University, Taipei 106, Taiwan
| | - Chong-Yi Liou
- Graduate Institute of Commutation Engineering, National Taiwan University, Taipei 106, Taiwan
| | - Yuan-Mou Mao
- School of Medicine, National Taiwan University, Taipei 106, Taiwan
| | - Wang-Huei Sheng
- School of Medicine, National Taiwan University, Taipei 106, Taiwan
| | - Shau-Gang Mao
- Graduate Institute of Commutation Engineering, National Taiwan University, Taipei 106, Taiwan
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