A Swarm Fire-Fighting Robots Dynamic Control Model for Mine Fires

Fire poses a significant threat to human activities and industrial production, particularly in large-scale industrial settings such as mining operations. This paper proposes a control model for swarm fire-fighting robots to mitigate the impacts and risks associated with fires. The proposed model can dynamically adjust the number of fire-fighting robots according to the severity of multiple fire points to efficiently fight fires in a cooperative manner. By adopting the model, more fire-fighting robots are allocated to severe fire points, while fewer robots are allocated for less critical fire points. The approach prevents uneven deployment, which could lead to out-of-control fires or unutilised resources.

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Publication Details

Published
2025-03-20
DOI
https://doi.org/10.1109/iccae64891.2025.10980495
Citations
2
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
2.61

Funders

Controls
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article

A Swarm Fire-Fighting Robots Dynamic Control Model for Mine Fires

Xuebo Chen, Chenyang Li, Peng Chen
2 citations
Fire Detection and Safety Systems
2.61
article

A Swarm Fire-Fighting Robots Dynamic Control Model for Mine Fires

Xuebo Chen, Chenyang Li, Peng Chen
article en
2 citations

Abstract

Fire poses a significant threat to human activities and industrial production, particularly in large-scale industrial settings such as mining operations. This paper proposes a control model for swarm fire-fighting robots to mitigate the impacts and risks associated with fires. The proposed model can dynamically adjust the number of fire-fighting robots according to the severity of multiple fire points to efficiently fight fires in a cooperative manner. By adopting the model, more fire-fighting robots are allocated to severe fire points, while fewer robots are allocated for less critical fire points. The approach prevents uneven deployment, which could lead to out-of-control fires or unutilised resources.

University of Science and Technology Liaoning (CN), Box Hill Institute (AU)
National Natural Science Foundation of China
Openalex Percentile: Top 12%
Fire Detection and Safety Systems
2.61
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