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• W2739280912 abstract "This paper presents a fire heading estimation for solving the autonomous navigation problem of a firefighting robot in smoke-filled indoor fire environment. In smoke-filled fire environments, firefighters and firefighting robots experience difficulty maintaining direction while finding the fire source. To solve this, the statistical texture features in thermal images were analyzed and fused by using Bayesian estimation to compute the vertical and horizontal fire heading. For its validation, a large-scaled test-bed was built with a hallway and two rooms, with one of the rooms having a real size fire generating dense and dark smoke. The proposed method probabilistically computed the fire-heading toward the entrance of the hallway then guided the robot to the room with the actual fire, all while navigating in a smoke-filled situation. The experimental results have demonstrated the effectiveness of this method in indoor fire environments." @default.
• W2739280912 created "2017-07-31" @default.
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• W2739280912 date "2017-05-01" @default.
• W2739280912 modified "2023-09-30" @default.
• W2739280912 title "Bayesian estimation based real-time fire-heading in smoke-filled indoor environments using thermal imagery" @default.
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• W2739280912 doi "https://doi.org/10.1109/icra.2017.7989613" @default.
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