Vision-Based Robotic Manipulation of Flexible PCBs

Recently, increasing demands on automatic soldering of flexible printed circuit boards (PCBs) have been reflected in the fast expanding computer, communication, and consumer electronics manufacturing. However, the deformation of flexible PCBs results in the changing shape and hence the varying position of solder pads on flexible PCBs under applied forces, which opens up challenges for robotic soldering of flexible PCBs. This paper presents a vision-based control scheme for robotic soldering of flexible PCBs. The proposed controller enables the robot to automatically contact, then actively deform the flexible PCB into a desired configuration, such that the well-deformed PCB can be soldered in an automatic soldering machine. Both operations of contacting and active deformation are smoothly integrated into a single continuous controller and automatically transited by assessing the physical contact online. Neural-network techniques are employed to approximate the unknown deformation model and the uncalibrated camera model. The dynamic stability of the closed-loop system is rigorously proved with Lyapunov methods, and experimental results are presented to illustrate the performance of the proposed controller.