Fast Collision Detection Method Based on Whale Optimization Algorithm in Virtual Maintenance

In response to the problems of slow detection rate and low detection accuracy of traditional collision detection algorithms in complex virtual maintenance environment, a fast collision detection algorithm based on whale algorithm is proposed and applied to virtual maintenance environment. Firstly, the collision detection of objects is carried out by using hierarchical bounding box, and the objects that may collide are screened. Secondly, the collision detection problem of 3D model is transformed into a nonlinear optimization problem of distance between feature pairs in 2D discrete space. Finally, the whale optimization algorithm is used to solve the problem, and the elite-ordinary strategy is introduced, so that the whale individuals can choose the best way to move, so as to improve the detection efficiency of the algorithm. In order to avoid the algorithm falling into the local optimal solution, the mutation step factor is used to enhance the levy flight mechanism, and the adaptive inertia weight is added to make the whale individual dynamically adjust the ability to get rid of the initial position, so as to improve the detection accuracy of the algorithm. The simulation results show that the algorithm has higher collision detection accuracy and less detection time than the commonly used collision detection algorithm after introducing the elite-ordinary strategy.