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基于视觉扫描生成巡检任务的机器人巡检方法

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目前工业场景巡检机器人的巡检点设置是人员手动设置的.考虑到现场环境复杂,通常巡检点的数量庞大,设置任务耗费大量人力和时间,且一旦巡检点的设备改变,还得人工增加或删除巡检点,提出基于自动视觉扫描生成巡检任务的机器人巡检方法,利用机器人扫描环境的视频流,将所有图片送入到YOLOv4目标检测网络进行解析和筛选,并运用SIFT匹配方式去掉重复目标,可以自动生成复杂现场设备的巡检点.在隧道电缆的机器人巡检项目中应用此方法,相比于人工设置方式,提高效率90%以上.
Robot Inspection Method Based on Visual Scanning to Generate Inspection Tasks
At present,the patrol point setting for industrial scene patrol robots is manual setting of personnel.Considering that the number of patrol points is usually large in the complex environment of the site,setting tasks consumes a lot of manpower and time,and once the equipment of the patrol points changes,manually adding or deleting patrol points is needed,a robot patrol method based on au-tomatic visual scanning to generate patrol tasks was proposed.Using the video stream of the robot scanning environment,all pictures were sent to YOLOv4 target detection network for analysis and screening,and the SIFT matching method was used to remove duplicate targets,then patrol points could automatically generated for complex field equipment.This method was applied in the robot patrol projects of tunnel cable.Compared with manual setting mode,it can improve the efficiency over 90%.

patrol robotautomatic patrol point settingYOLOv4 target detectionSIFT matching

孟浩、安福旺、吉力特

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内蒙古京能盛乐热电有限公司,内蒙古呼和浩特 011518

巡检机器人 自动巡检点设置 YOLOv4目标检测 SIFT匹配

2024

机床与液压
中国机械工程学会 广州机械科学研究院有限公司

机床与液压

CSTPCD北大核心
影响因子:0.32
ISSN:1001-3881
年,卷(期):2024.52(3)
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