Abstract

This paper presents the design and implementation of a practical visual servo. The visual servo has been designed for pose correction of an end-effector that is placed wrongly away from the test point on a printed circuit board (PCB). It is widely acknowledged that the error could be attributed to the connecting joints of robot arms, angular errors, geometric model, and/or camera projection model. In the automated fault insertion test (AFIT), the typical difficulty encountered by a robot is to servo and place the probe tip accurately on the targeted test point, i.e., the conductive pad on the PCB. Conventionally, touch and sense with a probe tip has been utilized. Upon detection of a failure, the visual servo is triggered and the robot literally looks through a camera and re-attempts with the use of visual information from the camera. Currently, no clearly defined specifications in carrying out feature extraction exist and thereby the test point detection as it is not cost-effective to designate part of PCB footprint as the test point separately from the main design to accommodate visual sensing. As a result, various kinds of test points have been implanted into PCB industrial design. This research work requires building of a custom knowledge base of the test point features to support image recognition. Furthermore, the operational factors in industrial manufacturing, e.g., head structure maintenance, the replacement of end-effectors and the changes of projection parameters caused by hardware adjustment, impact the accuracy of the probe placement. These factors cause the original geometric model to shift from the original configuration and thus errors. This research paper proposes the practical design of a closed-looped visual servo to address the issues of precision error, image feature extraction, and manufacturing factors. Besides, the paper details the findings from the design phase to the implementation phase.

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