OBBTree: A Hierarchical Structure for Rapid Interference Detection

Stefan Gottschalk
University of North Carolina at Chapel Hill

Ming Lin
US Army Research Office
University of North Carolina at Chapel Hill

Dinesh Manocha
University of North Carolina at Chapel Hill

We present a data structure and an algorithm for efficient and exact interference detection amongst complex models undergoing rigid motion. The algorithm is applicable to all general polygonal models. It pre-computes a hierarchical representation of models using tight-fitting oriented bounding box trees (OBBTrees). At runtime, the algorithm traverses two such trees and tests for overlaps between oriented bounding boxes based on a separating axis theorem, which takes less than 200 operations in practice. It has been implemented and we compare its performance with other hierarchical data structures. In particular, it can robustly and accurately detect all the contacts between large complex geometries composed of hundreds of thousands of polygons at interactive rates.

Papers Main Page ACM SIGGRAPH Contact us about:
Papers | This Web Site

Final SIGGRAPH 96 Web site update: 25 October 1996.
For complete information on the next conference and exhibition, see: http/