一种消防机器人火源定位及自动跟踪系统  

A system of flame location and automatic tracking for fire-fighting robot

作　　者：郝永奇 刘晓铭[1] 张静[1] Hao Yongqi;Liu Xiaoming;Zhang Guofang(NARI Group Corporation(State Grid Electric Power Research Institute),NARI Technology Co.,Ltd.,Jiangsu Nanjing 211106,China)

机构地区：[1]南瑞集团(国网电力科学研究院)国电南瑞科技股份有限公司,江苏南京211106

出　　处：《消防科学与技术》2023年第7期966-971,共6页Fire Science and Technology

基　　金：国电南瑞科技项目资助(524608220021)。

摘　　要：传统的消防机器人受限于火源检测和定位技术,检测和定位精度受环境影响较大,导致效果较差,部署复杂且智能化程度不高。针对这一问题,基于深度学习,结合视频图像处理技术,设计并实现了一套火焰检测、定位及自动跟踪灭火系统。该系统采用高实时深度学习模型进行火灾检测,通过计算和比较图像的结构相似度,结合火焰的动态特征对误报进行排除,进一步提高了检测精度。同时,引入基于冗余图像分割的二次检测,提高小目标火源的检测率,有效增加了消防机器人的检测灭火距离。此外,利用单目相机对火源进行定位跟踪,部署简单。试验结果表明,该系统提升了火焰检测的精度和检测距离,具有良好的实时性,能够满足复杂环境的消防机器人自动灭火。Traditional fire-fighting robots are limited by fire detection and location technology.The detection and location accuracy are greatly affected by the environment,resulting in poor performance,complex deployment and low intellectualization.Against this problem,a set of automatic fire location and tracking system is designed and implemented based on deep learning,which is also integrated with video image processing technology.The system uses a high-real-time deep learning model for fire detection,and it eliminates false alarms by calculating and comparing the structural similarity ratio of the images,as well as combined with the dynamic characteristics of the flame,thereby further improving the detection accuracy.At the same time,the system introduces the secondary detection based on redundant image segmentation to improve the detection rate of small target fire and effectively increase the detection distance of fire-fighting robots.Additionally,our work facilitates the deployment by taking advantage of the monocular camera to locate and track the fire source.Experimental results have demonstrated that the system improves the accuracy and detection distance of flame detection,and has good real-time performance.These results also allow the proposed system to be a prime candidate for fire-fighting robots in some complex environments.

关 键 词：火焰检测 视频图像 火源定位 自动跟踪 深度学习 消防机器人 

分 类 号：X913.4[环境科学与工程—安全科学] TP183[自动化与计算机技术—控制理论与控制工程]