Image Space Collision Detection

This thesis describes the author's work on Collision Decetion. The research focused on Image Space Collision Detection.Realtime collision detection is one of the most important problems in the fields of robotics,computer animation, and virtual reality,etc. Its fundamental task is to detect whether there are contacts or penetrations between two or among multiple objects. Though there have been many research achievements on solving the problem of collision detection,this problem is yet to be solved with the emergence of such techniques as virtual reality, and the demands of real time interactivity and realistic simulation of motions of virtual objects.The core of the problem is to improve the speed of collsion detection efficiently.Based on the intensive survey and comprehensive analyses of various approaches to collision detection, several algorithms have been analyzed, this paper expanded and implemented and verified to explore an image space collision detection algorithm. This algorithm explore the possibility of speeding up the process of collision detection on how to use the high computing power of graphics hardware.First the algorithm decompose the surfaces of an object into a list of convex pieces and organize the convex pieces into a binary tree with nodes composed of convex pieces, and by adopting triangle strip compression,which is a kind of real time rendering techniques. Furthermore, with the programmable function of graphics hardware ,we analysis the character of PCS, make good use of new way of culling to reduce the intersection test .At last,the algorithm realize the migration of collision detection to programmable GPU,it can balance the load between CPU and GPU, during this process ,the OBB will be used to improve the speed of collision detection.Using VC++ and OpenGL,image space collision detection was realized on personal computer with PentiumⅤ2.66GHz,778M memory.