Surface Patch Primitive Based Object Modeling from CAD Data

Abstract

For manufacturing automation, for instance, the robotic automation of automobile sub-assembly, CAD data serves as DB offering the geometric information of parts essential for robotic manipulation. However, a direct application of CAD for the robotic manipulation of parts may be of an issue, due to the fact that the particular format of the CAD data available, e.g., STL, does not directly provide certain geometric entities such as surface patch primitives and/or features that are required for robotic manipulation. In this paper, we present a novel method for extracting geometric primitives and/or features, such surface patch primitives as planar, cylindrical, conic, and spherical patches, from the STL format of CAD data, such that an industrial part/object can be represented as a logical sum of these surface patch primitives extracted. This surface patch primitive based modeling makes the automated reasoning involved in the recognition and pose estimation, as well as the grasp planning, of parts/objects easy to be done. The proposed method is applied to various CAD data samples for experimentation: the results demonstrate the reliability as well as the computational efficiency of the proposed method in the extraction of surface patch primitives.