Toward the Accurate Coverage of Aspheric Surfaces Using Two-Dimensional Scanning Paths for Minimizing Regular Errors

This paper describes a two-dimensional tool-path planning model for minimizing the regularly distributed errors or mid-frequency errors during computer controlled optical surfacing (CCOS) by optimally connecting different tool-path segments. The model was established based on a neuro-fuzzy algorithm, a path neighborhood function which is defined as a victorious output element calculated in a self-organization way, then, the optimum material removal function with a modified weight was derived. The material removal function was studied theoretically and the results of simulation present a Gaussian distribution feature. Discrete removal points and optimized tool-path grid were simulated. Finally, an experiment involving a parabolic mirror was performed for residual error removal and the two-dimensional tool-path planning algorithm was found to be valid.