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- W2022742521 abstract "In this paper we tackle the task of picking parts from a bin (bin-picking task), employing a 6-DOF manipulator on which a single hand-eye camera is mounted. The parts are some cylinders randomly stacked in the bin. A Quasi-Random Sample Consensus (Quasi-RANSAC) ellipse detection algorithm is developed to recognize the target objects. Then the detected targets' position and posture are estimated utilizing camera's pin-hole model in conjunction with target's geometric model. After that, the target which is the easiest one to pick for the manipulator is selected from multi-detected results, and tracked while the manipulator approaches it along a collision-free path which is calculated in work space. At last, the detection accuracy and run-time performance of the Quasi-RANSAC algorithm is presented and the final position of the end-effecter is measured to describe the accuracy of the proposed bin-picking visual servoing system." @default.
- W2022742521 created "2016-06-24" @default.
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- W2022742521 date "2010-10-01" @default.
- W2022742521 modified "2023-09-23" @default.
- W2022742521 title "Ellipse Detection Based Bin-Picking Visual Servoing System" @default.
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- W2022742521 doi "https://doi.org/10.1109/ccpr.2010.5659176" @default.
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