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Solpen: An Accurate 6-DOF Positioning Tool for Vision-Guided Robotics

Trung-Son Le, Quoc‐Viet Tran, Xuan-Loc Nguyen, Chyi‐Yeu Lin

发表年份
2022
引用次数
8
访问权限
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摘要

A robot trajectory teaching system with a vision-based positioning pen, which we called Solpen, is developed to generate pose paths of six degrees of freedom (6-DoF) for vision-guided robotics applications such as welding, cutting, painting, or polishing, which can achieve a millimeter dynamic accuracy within a meter working distance from the camera. The system is simple and requires only a 2D camera and the printed ArUco markers which are hand-glued on 31 surfaces of the designed 3D-printed Solpen. Image processing techniques are implemented to remove noise and sharpen the edge of the ArUco images and also enhance the contrast of the ArUco edge intensity generated by the pyramid reconstruction. In addition, the least squares method is implemented to optimize parameters for the center pose of the truncated Icosahedron center, and the vector of the Solpen-tip. From dynamic experiments conducted with ChArUco board to verify exclusively the pen performance, the developed system is robust within its working range, and achieves a minimum axis-accuracy at approximately 0.8 mm.

关键词

Artificial intelligenceComputer visionRoboticsMachine visionComputer scienceEnhanced Data Rates for GSM EvolutionPyramid (geometry)RobotMathematics

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