This project is centered on three-dimensional spatial reasoning and its applications in intelligent engineering systems. Theories and techniques from the fields of geometric modeling and artificial intelligence (AI) are integrated so as to attack difficult problems that arise in design, manufacturing and other activities in the life cycle of mechanical and electromechanical products. The main body of the research is a natural sequel to previous, National Science Foundation supported work on automatic recognition of machinable features, and on accessibility analysis for the inspection of mechanical parts with Coordinate Measuring Machines (CMMs). USC's feature recognizer will be integrated downstream, with experimental process planners and with commercial NC (Numerical Control) cutter-path generators for driving machine tools. It will also be integrated upstream, with feature-based design systems. The existing feature finder is very promising because it can handle complex volumetric interactions between features, and produces removal volumes that satisfy stringent conditions for machinability. It will be redesigned so as to operate incrementally, thereby providing immediate manufacturing feedback to a designer. It will also be extended so as to extract the geometric information required by process planners and NC code generators. Research on inspection planning will seek to produce, fully automatically, complete programs for driving CMMs (and potentially other equipment such as laser probes), given toleranced solid models of mechanical parts. Dimensional inspection is closely related to tolerancing, and will build upon on-going work at USC on the semantics of tolerance specifications. Issues of measurement interpretation (soft gaging) also will be addressed.
