Particle swarm optimization for constrained circular-arc/line-segment fitting of discrete data points. (2nd January 2018) - Shi, Xuefei; Chen, Hao
Abstract: In this paper, a new non-gradient-based optimization scheme is designed for constrained circle–circle/circle–line fitting of discrete data points. It contains two important technical components: (a) constrained least-squares fitting of circular arcs and line segments, and (b) specially designed particle swarm algorithm for optimal corner/edge points. Our approach is developed for both two-dimensional and three-dimensional cases. The results of numerical computation demonstrate the better performance of the proposed approach, compared to the conventional methods. It can be used for the accurate determination of sharp edges in the form of circular arcs and/or line segments measured in high-precision inspection and manufacturing.