No abstract

The Grating and Filter Wheel Mechanisms of the JWST NIRSpec instrument allow for reconfiguration of the spectrograph in space in a number of NIR sub-bands and spectral resolutions. Challenging requirements need to be met simultaneously including high launch loads, the large temperature shift to cryo-space, high position repeatability and minimum deformation of the mounted optics. The design concept of the NIRSpec wheel mechanisms is based on the ISOPHOT Filter Wheels but with significant enhancements to support much larger optics. A well-balanced set of design parameters was to be found and a considerable effort was spent to adjust the hardware within narrow tolerances.

One of the key issues for a successful inspection process is the determination of the necessary number of cameras and their respective positions given a specific inspection task and a geometric model of the inspected work-piece and its surroundings. In the last decades, a number of approaches concerning camera positioning strategies have been proposed. Generally, these approaches define an inspection task in terms of good visibility of certain features on the surface of the inspected objects. However, these approaches neither provide general means to include arbitrary inspection requirements, nor do they minimize the number of required cameras. Others use only hard constraints to determine the area of feasibility for certain task requirements. To overcome these shortcomings, we propose a model-based approach to optimize one or more camera positions by optimizing cost-functions derived from the inspection task. The goal is to use a minimum number of cameras / camera positions to fulfill the inspection task. Feature-visibility is represented using a novel concept: the visibility map. It can be calculated quickly by using a projective approach, consumes little storage memory and allows for quick feature-visibility checks. The system is evaluated on several examples using real inspection tasks from current production processes.

Abstract. In this paper, we introduce a novel model-based visibility measure for geometric primitives called visibility map. It is simple to calculate, memory efficient, accurate for viewpoints outside the convex hull of the object and versatile in terms of possible applications. Several useful properties of visibility maps that show their superiority to existing visibility measures are derived. Various example applications from the automotive industry where the presented measure is used successfully conclude the paper.

Quality assurance programs of today's car manufacturers show increasing demand for automated visual inspection tasks. A typical example is just-in-time checking of assemblies along production lines. Since high throughput must be achieved, object recognition and pose estimation heavily rely on offline preprocessing stages of available CAD data. In this paper, we propose a complete, universal framework for CAD model feature extraction and entropy index based viewpoint selection that is developed in cooperation with a major german car manufacturer.