In complex virtual environment

where there are massive moving objects

collision detection would become the bottle-neck of system performance. To promote the computation efficiency in such case

a fast N-body collision detection algorithm

USSCD

is proposed

which is based on uniform spatial subdivision. In this algorithm

the computation complexity is reduced with a hybrid scheme

first

the object space is uniformly subdivided into a series of voxels; then

collision detection

based on the scheme of sorting-based sweep and prune

is performed within each voxel. Based on distribution density of objects

an optimal method is proposed to compute the size of voxels in uniform space subdivision

for a special class of collision detection algorithms

this method can lead to minimum computation complexity. USSCD was implemented

and compared with I-COLLIDE through a serial of tests. The results show that USSCD is superior in performance when massive objects are uniformly distributed. Moreover

the performance of USSCD is more stable than that of I-COLLIDE in consideration of variable correlation between objects.