Research on automatic opening tunnel fire door method by patrol robot in dark environment

Chong Li; Qihui Cui; Gengshuo Liu; Qi Wang; Song Ma; Guodong Zhu; Rui Guo

doi:10.1117/12.2646904

7 September 2022 Research on automatic opening tunnel fire door method by patrol robot in dark environment

Chong Li, Qihui Cui, Gengshuo Liu, Qi Wang, Song Ma, Guodong Zhu, Rui Guo

Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 123292I (2022) https://doi.org/10.1117/12.2646904
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China

Abstract

The cable patrol patrol robot can distinguish the fire door by image recognition technology and realize the function of crossing the fire door autonomously. However, the effect of image recognition is greatly affected by light intensity. In some cable tunnels, the dim environment makes the effect of image recognition fire door poor, which seriously affects the passage of robots. In order to improve the identification accuracy of fire door in dim environment, a method of tunnel fire door identification by patrol robot in dim environment was proposed. Firstly, the original image was preprocessed, and the image enhancement technology was mainly used to enhance the details of the collected image through guided filtering. The saliency detection algorithm based on feature clustering and multi-scale fusion can effectively reduce the interference of background information and false target, and obtain the feature image of target image. A target recognition network based on improved YOLO-V4 was adopted, which added one auxiliary network, which can effectively improve the performance of the whole feature extraction network. The attention mechanism was adopted to fuse the feature information of the auxiliary network and the backbone network, which enhanced the effective information channel, suppressed the invalid information channel, and improved the efficiency of network recognition. The experimental results show that this method can improve the accuracy of image recognition in dim environment and effectively solve the problem that patrol robot cannot accurately identify the fire door due to insufficient light.

Citation Download Citation

Chong Li, Qihui Cui, Gengshuo Liu, Qi Wang, Song Ma, Guodong Zhu, and Rui Guo "Research on automatic opening tunnel fire door method by patrol robot in dark environment", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 123292I (7 September 2022); https://doi.org/10.1117/12.2646904

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KEYWORDS

Image enhancement

Image fusion

Target detection

Detection and tracking algorithms

Feature extraction

Image filtering

Target acquisition

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