Research on Robot Positioning and Grasping Based on Improved YOLOv3
Aiming at the problems of poor positioning and low grasping efficiency of industrial parts in the manipulator grasping assembly task of visual guidance positioning,an improved YOLOv3 intelligent grasp-ing system solution is proposed to realize the intelligent of industrial parts from object detection to automat-ic grasping.First,in order to improve the detection performance of small targets and crowded targets,an im-proved YOLOv3 target detection network is proposed.Secondly,data collection and training are carried out on industrial parts to realize the target recognition and positioning of the parts.Finally,through camera cali-bration and hand-eye calibration,the transformation from the image coordinate system to the world coordi-nate system is realized,the world coordinates of the grasped object are obtained,the grasping plan of the manipulator is carried out,and the grasping of the target object is completed.In the experiment,the Kinect V2 camera and the UR3 six-axis collaborative manipulator were used to form a grasping experiment plat-form,and the positioning and grasping experiments of the target parts were carried out respectively.The ex-perimental results show that the improved YOLOv3 adds the fourth layer of feature-scale target detection,which improves the detection performance of small targets and crowded targets.The grasping system accu-rately locates the parts and successfully grasps them.
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