The proposed research addresses the development of capacitive proximity sensor arrays that can detect geometric features of interest such as edges of surfaces, locations of holes, spatial angles of workpieces relative to an end-effector, and distance between end- effectors and workpiece, while avoiding the extensive computing requirements and other problems typically associated with machine vision systems. The project will also explore the use of this technique in a fully automated surface-quality transducer system which will allow the quantitative determination and characterization of surface profiles and defects on technical surfaces, independent of the optical and magnetic properties of the surface. The transducer will be capable of quantitatively determining local and average surface roughness as well as depth and size of surface flaws. The sensor consists of a thin short lead embedded in a hard ceramic substrate, and is therefore rugged and can, due to its small size, be configured to almost any desired shape in order to examine hard-to-reach surfaces.
