IRI-9414523 Michael M. Marefat University of Arizona $78,552 - 12 mos. Spatial Reasoning for Machine Understanding of Solid Models This is the first year funding of a three-year research project with the objectives of studying and developing geometric reasoning mechanisms and knowledge representation methods for modeling and recognition of semantic shape features that will be useful in industrial design and manufacturing. A person or a machine that is going to perceive objects in order to interact with them in any way must do more than see the objects; it is necessary to recognize them as what they are, to attach a meaning to them. Actually seeing the objects as individual items with particular shapes and features is part of perception, and involves geometric reasoning. Attaching meaning to the objects means that there must be an internalknowledge representation for what is significant about them. A mapping from a set of geometric features to a meaning in terms of the knowledge representation is called semantics, after the analogous mapping in language. As the product life cycles become shorter and product variety increases, it is crucial to minimize the lag period between the start of a product's design and the time it is produced. This project includes applying the developed geometric reasoning models and mechanisms to solve important issues in machine understanding of designs, automated generation of process planning strategies, and automated visual inspection based on solid models. Initial promising results have been obtained on these problems. Further investigation will be performed systematically to develop the concepts and the mechanisms. In addition, the application of the concepts and mechanisms to the development of information driven intelligent integrated environments for flexible design and production will be studied.
