Constraint-based feature recognition: handling non-uniqueness in feature interactions

Ming Hsuan Yang, Michael M. Marefat

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations

Abstract

The feature recognition problem is formulated as a geometric constraint satisfaction problem (GCSP), in which variables are the faces in the delta volume, the possible feature classifications determine values for the variables, and the constraints are the geometric and topological properties between the variables. A novel representation language is proposed to encode more, and somewhat redundant, information about geometric and topological properties in form features. The redundant information adds more constraints amongst objects in feature interactions and thus helps in feature recognition. Moreover, the language can be extended to represent new features.

Original languageEnglish (US)
Pages (from-to)1505-1510
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
Volume2
StatePublished - 1996
EventProceedings of the 1996 13th IEEE International Conference on Robotics and Automation. Part 1 (of 4) - Minneapolis, MN, USA
Duration: Apr 22 1996Apr 28 1996

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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