Abstract Minimal Hierarchical Collision Detection ∗

We present a novel bounding volume hierarchy that allows for extremely small data structure sizes while still performing collision detection as fast as other classical hierarchical algorithms in most cases. The hierarchical data structure is a variation of axis-aligned bounding box trees. In addition to being very memory efficient, it can be constructed efficiently and very fast. We also propose a criterion to be used during the construction of the BV hierarchies is more formally established than previous heuristics. The idea of the argument is general and can be applied to other bounding volume hierarchies as well. Furthermore, we describe a general optimization technique that can be applied to most hierarchical collision detection algorithms. Finally, we describe several box overlap tests that exploit the special features of our new BV hierarchy. These are compared experimentally among each other and with the DOP tree using a benchmark suite of real-world CAD data. Keywords: Interference detection, virtual prototyping, hierarchical partitioning, hierarchical data structure, shape approximation, physically-based modeling, R-trees.