Feature-based five-axis path planning method for robotic additive manufacturing

Abstract

Additive manufacturing has been developed for decades and attracts significant research interests in recent years. Usually, the stereolithography tessellation language format is employed in additive manufacturing to represent the geometric data. However, people gradually realize the inevitable drawbacks of the stereolithography tessellation language file format, such as redundancy, inaccuracy, missing of feature definitions, and lack of integrity. In addition, it is almost impossible to apply the simple polygonal facet representation to the five-axis manufacturing strategy. Hence, there are quite few researches and applications on the five-axis additive manufacturing, in spite of its common applications in the subtractive machining. This article proposes a feature-based five-axis additive manufacturing methodology to enhance and extend the additive manufacturing method. The additive manufacturing features are defined and categorized into two5D_AM_feature and freeform_AM_feature. A feature extraction method is proposed that can automatically recognize the additive manufacturing features from the input model. Specially for the freeform_AM_feature, a five-axis path planning method is proposed and split into three stages: (1) offset the reference surface, (2) spatially slice the freeform layers, and (3) generate the toolpaths for each freeform layer. Real additive manufacturing five-axis toolpaths can be obtained using the proposed algorithm that performs as a secondary developed plug-in in the CATIA® environment. A robotic additive manufacturing system is constructed for the implementation of the five-axis additive manufacturing tasks, which are generated by the proposed algorithms and post-processed after simulation and off-line programming. Some examples are printed to validate the feasibility and efficiency of the proposed method.