Digital image approach to tool path generation for surface machining

Abstract

Conventional tool path generation algorithms are usually dependent to the surface geometry and thus case-sensitive. A specific tool path planning method for regular parametric surfaces cannot directly handle a triangular mesh surface, and vice versa. Presented in this paper is a unified digital image representation of a surface, along with a general process of tool path generation and optimization directly based on such representation. Regarding different objectives and utilities, three typical digital images are introduced to represent a projectable surface. Each digital image induces a uniform discrete scalar/vector field indicating the surface geometric property, which can be further applied to the cutter contact curve generation, tool orientation determination, and the cutting simulation tasks. Preliminary examples give a sneak peek of the capability of the proposed method. It is observed that, instead of utilizing geometry-based algorithm, some global optimization task of the tool path is transformed into finding a proper convolutional kernel and its parameter for the image processing. Though more investigation is worth spending in the future, the proposed approach inaugurates a standard and effective way to facilitate the tool path generation and optimization task for surface machining.