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Comparing Position- and Image-Based Visual Servoing for Robotic Assembly of Large Structures

Yuan-Chih Peng, Devavrat Jivani, Richard J. Radke, John T. Wen

发表年份
2020
引用次数
12

摘要

This paper considers image-guided assembly for large composite panels. By using fiducial markers on the panels and robot gripper mounted cameras, we are able to use an industrial robot to align the panels to sub-millimeter accuracy. We considered two commonly used visual servoing schemes: position-based visual servoing (PBVS) and image-based visual servoing (IBVS). It has been noted that IBVS possesses superior robustness with respect to the camera calibration accuracy. However, we have found that in our case, PBVS is both faster and slightly more accurate than IBVS. This result is due to the fact that the visual servoing target in the image plane is derived from a reference target, which depends on the accuracy of the camera model. This additional dependency essentially nullifies the robustness advantage of IBVS. We also implemented a simple scheme to combine inputs from multiple cameras to improve the visual servoing accuracy. Both simulation and experimental results are included to show the effectiveness of visual servoing in an industrial setting.

关键词

Visual servoingComputer visionArtificial intelligenceRobustness (evolution)Computer scienceRobot

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