Arc approximation algorithm of spatial movements for industrial robots

Borisov, Oleg I.; Gromov, Vladislav S.; Pyrkin, Anton A.; Petranevsky, Igor V.; Klyunin, Alexey O.; Bobtsov, Alexey A.

doi:10.1109/iecon.2017.8216581

Cited by 1 publication

(1 citation statement)

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“…The path of robot movement was approximated by using three points to define a circle technique. Later in 2017, this technique was improved to apply in spatial movement [3]. Moreover, the velocity of the movement is increased while the size of code can be reduced.…”

Section: Introductionmentioning

confidence: 99%

An Approximation of Bézier Curves by a Sequence of Circular Arcs

Nuntawisuttiwong

Dejdumrong

2021

ITC

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Some researches have investigated that a Bézier curve can be treated as circular arcs. This work is to proposea new scheme for approximating an arbitrary degree Bézier curve by a sequence of circular arcs. The sequenceof circular arcs represents the shape of the given Bézier curve which cannot be expressed using any other algebraicapproximation schemes. The technique used for segmentation is to simply investigate the inner anglesand the tangent vectors along the corresponding circles. It is obvious that a Bézier curve can be subdivided intothe form of subcurves. Hence, a given Bézier curve can be expressed by a sequence of calculated points on thecurve corresponding to a parametric variable t. Although the resulting points can be used in the circular arcconstruction, some duplicate and irrelevant vertices should be removed. Then, the sequence of inner angles arecalculated and clustered from a sequence of consecutive pixels. As a result, the output dots are now appropriateto determine the optimal circular path. Finally, a sequence of circular segments of a Bézier curve can be approximatedwith the pre-defined resolution satisfaction. Furthermore, the result of the circular arc representationis not exceeding a user-specified tolerance. Examples of approximated nth-degree Bézier curves by circular arcsare shown to illustrate efficiency of the new method.

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Section: Introductionmentioning

confidence: 99%