基于YOLOv5算法的烟囱拆除机器人预留孔圆心定位模型OA

The utilization of reserved holes on the chimney wall for the lifting and locking of the chimney demolition robot can significantly enhance the working efficiency of the robot.A method is proposed for identifying and locating reserved holes on the chimney wall based on deep learning object detection technol-ogy.Firstly,the YOLOv5 deep learning network model is used to detect the approximate area of the reserved holes in the image,obtaining the coarse positioning information of the reserved holes.Then,the Gaussian filtering method is applied to remove isolated points and noise in this area.Subsequently,based on the coarse positioning information of the reserved holes,the Canny operator is used to extract the edge information of the reserved holes.Finally,the least squares-based elliptical fitting method is employed to obtain the center coordinates of the reserved holes,achieving precise positioning of the reserved holes and effectively reducing the impact of factors such as blurred target edges,similar object interference,and cir-cular distortion on the positioning accuracy of the reserved holes.The research results show that the mAP@0.5%of the YOLOv5s model reaches 99.5%,with a detection speed of 6.5 ms.In the simula-tion environment,the center positioning error is less than 0.8 pixels,which can effectively improve the reliability and efficiency of the lifting operation of the chimney demolition robot.