5 resultados para Computer-aided Design
em University of Queensland eSpace - Australia
Laboratory and in situ investigations of tracking cutters for computer-aided design of shearer drums
Resumo:
This paper describes a formal component language, used to support automated component-based program development. The components, referred to as templates, are machine processable, meaning that appropriate tool support, such as retrieval support, can be developed. The templates are highly adaptable, meaning that they can be applied to a wide range of problems. Some of the main features of the language are described, including: higher-order parameters; state variable declarations; specification statements and conditionals; applicability conditions and theories; meta-level place holders; and abstract data structures.
Resumo:
Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.