A fast contact detection algorithm insensitive to object sizes

Presents a new contact detection algorithm based on double-ended spatial sorting (DESS) that is insensitive to variations in object size. It was developed to address the problems that arise when objects with non-spherical geometry and non-uniform sizes are simulated using discrete element techniques. The algorithms applicable to general spatial reasoning problems. While techniques based on spatial hashing (sometimes called bining methods) perform well for objects of similar size, they degrade significantly when the objects vary in size. The DESS algorithm overcomes this problem by using a spatial sorting technique applied to both ends of the object's projection along each orthogonal axis. Discrete element test simulations comparing DESS and spatial hashing (NBS) are detailed. The results demonstrate that when object sizes vary significantly (size ratios greater than 8:1), DESS out performs NBS up to around 100,000 objects. It is noted, however, that the superior scaling properties of NBS will always outperform DESS for some large numbers of objects.