Real-Time Fire and Smoke Detection for Trajectory Planning and Navigation of a Mobile Robot
Mobile robots have many industrial applications, including security, food service, and fire safety. Detecting smoke and fire quickly for early warning and monitoring is crucial in every industrial safety system. In this paper, a method for early smoke and fire detection using mobile robots equipped...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
D. G. Pylarinos
2023-10-01
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| Series: | Engineering, Technology & Applied Science Research |
| Subjects: | |
| Online Access: | http://www.etasr.com/index.php/ETASR/article/view/6252 |
| _version_ | 1797660076708724736 |
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| author | Pham Van Bach Ngoc Le Huy Hoang Le Minh Hieu Ngoc Hai Nguyen Nguyen Luong Thien Van Tuan Doan |
| author_facet | Pham Van Bach Ngoc Le Huy Hoang Le Minh Hieu Ngoc Hai Nguyen Nguyen Luong Thien Van Tuan Doan |
| author_sort | Pham Van Bach Ngoc |
| collection | DOAJ |
| description | Mobile robots have many industrial applications, including security, food service, and fire safety. Detecting smoke and fire quickly for early warning and monitoring is crucial in every industrial safety system. In this paper, a method for early smoke and fire detection using mobile robots equipped with cameras is presented. The method employs artificial intelligence for trajectory planning and navigation, and focus is given to detection and localization techniques for mobile robot navigation. A model of a mobile robot with Omni wheels and a modified YOLOv5 algorithm for fire and smoke detection is also introduced, which is integrated into the control system. This research addresses the issue of distinct objects of the same class by assigning each object a unique identification. The implementation not only detects fire and smoke but also identifies the position of objects in three-dimensional space, allowing the robot to map its environment incrementally for mobile navigation. The experimental results demonstrate the high accuracy achieved by the proposed method in identifying smoke and fire.
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| first_indexed | 2024-03-11T18:24:33Z |
| format | Article |
| id | doaj.art-ec6b3f293e4444cbac199da72275aeac |
| institution | Directory Open Access Journal |
| issn | 2241-4487 1792-8036 |
| language | English |
| last_indexed | 2024-03-11T18:24:33Z |
| publishDate | 2023-10-01 |
| publisher | D. G. Pylarinos |
| record_format | Article |
| series | Engineering, Technology & Applied Science Research |
| spelling | doaj.art-ec6b3f293e4444cbac199da72275aeac2023-10-14T05:47:03ZengD. G. PylarinosEngineering, Technology & Applied Science Research2241-44871792-80362023-10-0113510.48084/etasr.6252Real-Time Fire and Smoke Detection for Trajectory Planning and Navigation of a Mobile RobotPham Van Bach Ngoc0Le Huy Hoang1Le Minh Hieu2Ngoc Hai Nguyen 3Nguyen Luong Thien4Van Tuan Doan 5Sefas Department, Space Technology Institute, Vietnam Academy of Science and Technology, VietnamSefas Department, Space Technology Institute, Vietnam Academy of Science and Technology, VietnamSefas Department, Space Technology Institute, Vietnam Academy of Science and Technology, VietnamSefas Department, Space Technology Institute, Vietnam Academy of Science and Technology, VietnamSefas Department, Space Technology Institute, Vietnam Academy of Science and Technology, VietnamHung Yen University of Technology and Education, VietnamMobile robots have many industrial applications, including security, food service, and fire safety. Detecting smoke and fire quickly for early warning and monitoring is crucial in every industrial safety system. In this paper, a method for early smoke and fire detection using mobile robots equipped with cameras is presented. The method employs artificial intelligence for trajectory planning and navigation, and focus is given to detection and localization techniques for mobile robot navigation. A model of a mobile robot with Omni wheels and a modified YOLOv5 algorithm for fire and smoke detection is also introduced, which is integrated into the control system. This research addresses the issue of distinct objects of the same class by assigning each object a unique identification. The implementation not only detects fire and smoke but also identifies the position of objects in three-dimensional space, allowing the robot to map its environment incrementally for mobile navigation. The experimental results demonstrate the high accuracy achieved by the proposed method in identifying smoke and fire. http://www.etasr.com/index.php/ETASR/article/view/6252mobile robotsrobot mappingsmoke and fire real-time detectiondynamic environmentlocalizationpresumptive environment |
| spellingShingle | Pham Van Bach Ngoc Le Huy Hoang Le Minh Hieu Ngoc Hai Nguyen Nguyen Luong Thien Van Tuan Doan Real-Time Fire and Smoke Detection for Trajectory Planning and Navigation of a Mobile Robot Engineering, Technology & Applied Science Research mobile robots robot mapping smoke and fire real-time detection dynamic environment localization presumptive environment |
| title | Real-Time Fire and Smoke Detection for Trajectory Planning and Navigation of a Mobile Robot |
| title_full | Real-Time Fire and Smoke Detection for Trajectory Planning and Navigation of a Mobile Robot |
| title_fullStr | Real-Time Fire and Smoke Detection for Trajectory Planning and Navigation of a Mobile Robot |
| title_full_unstemmed | Real-Time Fire and Smoke Detection for Trajectory Planning and Navigation of a Mobile Robot |
| title_short | Real-Time Fire and Smoke Detection for Trajectory Planning and Navigation of a Mobile Robot |
| title_sort | real time fire and smoke detection for trajectory planning and navigation of a mobile robot |
| topic | mobile robots robot mapping smoke and fire real-time detection dynamic environment localization presumptive environment |
| url | http://www.etasr.com/index.php/ETASR/article/view/6252 |
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