Real-Time Fire and Smoke Detection for Trajectory Planning and Navigation of a Mobile Robot
Received: 14 August 2023 | Revised: 25 August 2023 and 31 August 2023 | Accepted: 2 September 2023 | Online: 13 October 2023
Corresponding author: Pham Van Bach Ngoc
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.
Keywords:mobile robots, robot mapping, smoke and fire real-time detection, dynamic environment, localization, presumptive environment, robot navigation, object identification
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Copyright (c) 2023 Pham Van Bach Ngoc, Le Huy Hoang, Le Minh Hieu, Ngoc Hai Nguyen , Nguyen Luong Thien, Van Tuan Doan
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