Visual media are of great importance to designers. Understanding a new design, for example, often means understanding a drawing. From the perspective of artificial intelligence, this implies that automated knowledge acquisition in computer-aided design can productively occur using drawings as a knowledge source. However, this requires machines that are able to interpret design drawings.
I view the task of interpreting drawings as one of constructing a teleological model of the design depicted in the drawings, where the model enables causal and functional inferences about the depicted design. I have developed a novel analogical method for constructing a teleological model of a mechanical device from an unlabelled 2D line drawing. The source case is organized in a Drawing Shape Structure Behavior Function (DSSBF) abstraction hierarchy. This knowledge
organization enables the analogical mapping and transfer to occur at multiple levels of abstraction.
Given a target drawing and a relevant source case, my method of compositional analogy first constructs a graphical representation of the lines and the intersections in the target drawing, then uses the mappings at the level of line intersections to transfer the shape representations from the source case to the target. It next uses the mappings at the level of shapes to transfer the structural model of the device from the source to the target. Finally, the mappings from the source to the target structural model enable the transfer of behaviors and the functional specification from source to target, completing the analogy and yielding a complete DSSBF model of the input drawing. The Archytas system implements this method of compositional analogy and evaluates it in the domain of kinematic devices such as piston and crankshaft devices, door latches, and pulley systems.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/19791 |
| Date | 18 October 2007 |
| Creators | Yaner, Patrick William |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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