A Collision Detection Algorithm Based On Improved Quantum Particle Swarm Optimization

In the field of virtual reality, Collision Detection Technology was widely developed for improving the performance of 3D Graphics. Following rapid growth of virtual objects with complex shapes, conventional methods perform harder to effectively detect the collision. Facing the problem, we presented a collision detection algorithm based on improved quantum particle swarm optimization. Firstly, we converted the collision detection problem into nonlinear constrained optimization problem. Secondly, we employed the Euclidean distance to evaluate whether there was collision between two objects. Then, we improved the quantum particle swarm optimization (QPSO) algorithm by (1) using quantum Hε gate and quantum rotation gate in changing quantum probability amplitude, (2) changing the mutation operator with Quantum Hadamard Gate and (3) modifying constant Inertia Weight to random inertia weight. In the end, the results of numerical simulation and analysis were provided to verify the validity of our algorithm.