Efficient collision detection using bounding volume hierarchies of OBB-AABBs and its application

In computer graphics, collision detection is considered a key problem with important applications in related areas. In this research, we present an efficient algorithm for collision detection using a dual bounding hierarchy which consists of an oriented bounding box (OBB) tree enhanced with Axes-Aligned Bounding Box (AABB). The algorithm combines the compactness of the OBB and the efficient overlap test for AABB. The AABB test is applied firstly to eliminate distant objects efficiently. The remaining objects are in close proximity are tested using the separation axis of OBBs, where some separation axis are more effective and should be chosen first. We apply the efficient approach to the virtual acupuncture medical treatment systems, and the experimental results show that the new algorithm effectively reduces the query time and improve the computing efficiency with respect to the existing collection detection algorithms.