Pick-and-place robots are commonly used in modern industrial manufacturing. For complex devices/parts like camera modules used in smartphones, which contain optical parts, electrical components and interfacing connectors, the placement operation may not absolutely accurate, which may cause damage in the device under test during the mechanical movement to make good contact for electrical functions inspection. In this paper, we proposed an effective vision system including hardware and algorithm to enhance the reliability of the pick-and-place robot for autonomous testing memory of camera modules. With limited hardware based on camera and raspberry PI and using simplify image processing algorithm based on histogram information, the vision system can confirm the presence of the camera modules in feeding tray and the placement accuracy of the camera module in test socket. Through that, the system can work with more flexibility and avoid damaging the device under test. The system was experimentally quantified through testing approximately 2000 camera modules in a stable light condition. Experimental results demonstrate that the system achieves accuracy of more than 99.92%. With its simplicity and effectiveness, the proposed vision system can be considered as a useful solution for using in pick-and-place systems in industry.

翻译：拾放机器人广泛应用于现代工业制造中。对于智能手机摄像头模组等包含光学元件、电子组件及接口连接器的复杂器件/部件，其放置操作可能存在不绝对精准的情况，这可能导致在为实现电功能检测而进行机械运动接触过程中损坏被测器件。本文提出了一种包含硬件和算法的有效视觉系统，以提升用于摄像头模组存储功能自主测试的拾放机器人可靠性。基于摄像头和树莓派的有限硬件，并采用基于直方图信息的简化图像处理算法，该视觉系统能够确认供料盘中的摄像头模组是否到位以及测试插座中的摄像头模组放置精度。由此，系统可更灵活地工作并避免损坏被测器件。通过在稳定光照条件下对约2000个摄像头模组进行测试，实验量化验证了系统性能。实验结果表明，该系统准确率超过99.92%。凭借其简单性和有效性，所提出的视觉系统可被视为工业拾放系统中的一个实用解决方案。