2018
DOI: 10.1177/1729881418813805
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Trajectory planning method of robot sorting system based on S-shaped acceleration/deceleration algorithm

Abstract: To improve the sorting accuracy and efficiency of sorting system with large inertia robot, this article proposes a novel trajectory planning method based on S-shaped acceleration/deceleration algorithm. Firstly, a novel displacement segmentation method based on assumed maximum velocity is proposed to reduce the computational load of velocity planning. The sorting area can be divided into four parts by no more than three steps. Secondly, since the positions of workpieces are dynamically changing, a dynamic pred… Show more

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Cited by 19 publications
(10 citation statements)
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“…As for the traditional S-shaped ACC/DEC algorithm [16], [17], both the change of the velocity curve and acceleration curve are consecutive. It is a suitable ACC/DEC curve for high-speed motion which can avoid mechanical vibration and is applied in CNC system widely.…”
Section: A Modified S-shaped Acc/dec Curvementioning
confidence: 99%
“…As for the traditional S-shaped ACC/DEC algorithm [16], [17], both the change of the velocity curve and acceleration curve are consecutive. It is a suitable ACC/DEC curve for high-speed motion which can avoid mechanical vibration and is applied in CNC system widely.…”
Section: A Modified S-shaped Acc/dec Curvementioning
confidence: 99%
“…Generally, the acceleration and deceleration motion of the S-shaped curve, including seven or five stages of motion control, is described as follows [44]:…”
Section: Control Algorithm For Dummy's Motionmentioning
confidence: 99%
“…Shape identification of workpiece objects is an important issue in industrial applications due to high rate of production and automatic system efficiency. There are many references that discuss workpiece sorting [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. For tube material applications, the geometric features are measured by automated optical inspection technology then machine learning models, e.g., neural network (NN), support vector machine, and random forest, were used for sorting or identification [ 3 , 4 ].…”
Section: Introductionmentioning
confidence: 99%