Chaotic quantum ant optimization algorithm and its application on collision detection

Collision detection is very important to improve the truth and immersion in the virtual environment. Firstly the paper analyzes the problems that exist in traditional algorithms. Secondly the paper analyses the problem of collision detection in theory, and then converts the problem of the collision detection to the non-linear programming problem with restricted conditions. And then the chaotic quantum ant colony optimization algorithm is brought forward to resolve the problem. A proof of convergence for the algorithm is developed. Finally, the simulation test shows that the chaotic quantum ant optimization algorithm has much more effective impact on solving the extreme-value problem compared to the traditional genetic algorithm. It is feasible to use the algorithm in collision detection.