Journal of System Simulation ›› 2018, Vol. 30 ›› Issue (1): 62-68.doi: 10.16182/j.issn1004731x.joss.201801008

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Collision Detection Algorithm of Deformable Object Based on Snake Model Optimization

Li Zhao, Jin Yanxia, Qin Zhipeng, Ren Chao   

  1. School of Computer Science and Control Engineering, North University of China, Taiyuan 030051, China
  • Received:2015-12-08 Published:2019-01-02

Abstract: In view of the existing collision detection algorithm which is difficult to solve the collision of real-time and reality, an improved algorithm of collision detection was propsed based on deformable objects. The algorithm based on K-DOPs bounding box applied to update process used the improved PSO algorithm to optimize the Snake model boundary. The concave in collision region, the control point clusters and the center formed multi-linear swarm with the improved selection method and the ulti PSO algorithm. Experimental results show that the improved collision detection algorithm can accurate simulate object contour, simplify the bounding box to improve the efficiency of collision detection.

Key words: detection, (K-dops) bounding box, multi-linear swarm, particle swarm optimization algorithm, snake model

CLC Number: