本文提出一种基于机器视觉引导的工业机器人柔性装配系统,重点解决汽车发动机对接中精度与效率的矛盾。该系统通过高分辨率工业相机与六维力传感器的融合应用,结合YOLOv3目标检测算法与九点标定算法,实现部件亚像素级定位及动态误差补偿。试验结果表明,该系统在发动机曲轴装配中的定位精度可达0.05mm,单工位节拍时间控制在8s内,次品率较传统工艺降低80%。

This paper proposes a machine vision-guided flexible assembly system for industrial robots, focusing on resolving the precision-efficiency conflict in automotive engine docking. By integrating high-resolution industrial cameras with six-dimensional force sensors, and combining YOLOv3 object detection with nine-point calibration algorithms, the system achieves sub-pixel level component positioning and dynamic error compensation. Experimental results demonstrate that the system achieves 0.05mm positioning accuracy in engine crankshaft assembly, completes single-station operations within 8 seconds, and reduces defect rates by 20% compared to traditional processes.