Detection of classes of features for automated robot programming

Abstract

This paper presents an approach to detect classes of features that are relevant for automating spray painting. Using knowledge about the painting process a set of elementary geometries is defined, where each elementary geometry is related to a specific painting strategy. Hence all parts and part families containing these elementary geometries can be detected. After detection the paint strokes are automatically generated for robot programming. Specifically we show how free-form surfaces, cavities and rib sections are detected in the range image of the parts. Results of detecting these features on a large variety of parts are presented.