Sorting System Algorithms Based on Machine Vision for Delta Robot
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Graphical Abstract
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Abstract
To overcome the repeat shooting to workpieces by vision system in sorting process, an image deduplication algorithm based on time and workpieces' positions is proposed. The running time of the real-time sorting system is used as basis of each sorting module, and the predicted time that workpieces arrive at a fixed reference position is combined with its current location into a set of coordinates to uniquely identify a part. So the duplicate image information can be found and removed by comparing those coordinates periodically. At the same time, in order to improve sorting efficiency, a dynamic picking algorithm based on Newton-Raphson method is proposed. The non-linear mathematical model is established for workpiece tracking, which is solved by Newton-Raphson iteration. Finally, the proposed dynamic picking algorithm is verified by MATLAB. In prototype test the maximum sorting speed can reach 110 times per minute, mistaken-grab rate is lower than 2‰, missing-grab rate is 0, which proves that the algorithms can meet the real-time, the accuracy and the stability requirements.
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