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Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion †
Dams are important engineering facilities in the water conservancy industry. They have many functions, such as flood control, electric power generation, irrigation, water supply, shipping, etc. Therefore, their long-term safety is crucial to operational stability. Because of the complexity of the da...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070333/ https://www.ncbi.nlm.nih.gov/pubmed/32079361 http://dx.doi.org/10.3390/s20041097 |
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author | Zhang, Chao Zhan, Quanzhong Wang, Qi Wu, Haichao He, Ting An, Yi |
author_facet | Zhang, Chao Zhan, Quanzhong Wang, Qi Wu, Haichao He, Ting An, Yi |
author_sort | Zhang, Chao |
collection | PubMed |
description | Dams are important engineering facilities in the water conservancy industry. They have many functions, such as flood control, electric power generation, irrigation, water supply, shipping, etc. Therefore, their long-term safety is crucial to operational stability. Because of the complexity of the dam environment, robots with various kinds of sensors are a good choice to replace humans to perform a surveillance job. In this paper, an autonomous system design is proposed for dam ground surveillance robots, which includes general solution, electromechanical layout, sensors scheme, and navigation method. A strong and agile skid-steered mobile robot body platform is designed and created, which can be controlled accurately based on an MCU and an onboard IMU. A novel low-cost LiDAR is adopted for odometry estimation. To realize more robust localization results, two Kalman filter loops are used with the robot kinematic model to fuse wheel encoder, IMU, LiDAR odometry, and a low-cost GNSS receiver data. Besides, a recognition network based on YOLO v3 is deployed to realize real-time recognition of cracks and people during surveillance. As a system, by connecting the robot, the cloud server and the users with IOT technology, the proposed solution could be more robust and practical. |
format | Online Article Text |
id | pubmed-7070333 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70703332020-03-19 Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion † Zhang, Chao Zhan, Quanzhong Wang, Qi Wu, Haichao He, Ting An, Yi Sensors (Basel) Article Dams are important engineering facilities in the water conservancy industry. They have many functions, such as flood control, electric power generation, irrigation, water supply, shipping, etc. Therefore, their long-term safety is crucial to operational stability. Because of the complexity of the dam environment, robots with various kinds of sensors are a good choice to replace humans to perform a surveillance job. In this paper, an autonomous system design is proposed for dam ground surveillance robots, which includes general solution, electromechanical layout, sensors scheme, and navigation method. A strong and agile skid-steered mobile robot body platform is designed and created, which can be controlled accurately based on an MCU and an onboard IMU. A novel low-cost LiDAR is adopted for odometry estimation. To realize more robust localization results, two Kalman filter loops are used with the robot kinematic model to fuse wheel encoder, IMU, LiDAR odometry, and a low-cost GNSS receiver data. Besides, a recognition network based on YOLO v3 is deployed to realize real-time recognition of cracks and people during surveillance. As a system, by connecting the robot, the cloud server and the users with IOT technology, the proposed solution could be more robust and practical. MDPI 2020-02-17 /pmc/articles/PMC7070333/ /pubmed/32079361 http://dx.doi.org/10.3390/s20041097 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Chao Zhan, Quanzhong Wang, Qi Wu, Haichao He, Ting An, Yi Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion † |
title | Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion † |
title_full | Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion † |
title_fullStr | Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion † |
title_full_unstemmed | Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion † |
title_short | Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion † |
title_sort | autonomous dam surveillance robot system based on multi-sensor fusion † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070333/ https://www.ncbi.nlm.nih.gov/pubmed/32079361 http://dx.doi.org/10.3390/s20041097 |
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