Broad-phase collision detection using semi-adjusting BSP-trees

Abstract

The broad-phase step of collision detection in scenes composed of n moving objects is a challenging problem because enumerating collision pairs has an inherent O(n2) complexity. Spatial data structures are designed to accelerate this process, but often their static nature makes it difficult to handle dynamic scenes. In this work we propose a new structure called Semi-Adjusting BSP-tree for representing scenes composed of thousands of moving objects. An scheduling algorithm evaluates locations where the BSP-tree becomes unbalanced, uses several strategies to alter cutting planes, and defer updates based on their re-structuring cost. We show that the tree does not require a complete re-structuring even in highly dynamic scenes, but adjusts itself while maintaining desirable balancing and height properties.