Abstract
In order to improve the real-time of collision detection algorithm, this paper introduces particle swarm optimization (PSO), PSO simple and easy to operate, and search capability and convergence speed have a greater advantage. To reduce the random collision detection algorithm missed some of the interfering elements and to improve the accuracy of collision detection, using the OBB bounding box surrounding the basic geometric elements instead of the basic geometric elements characterized as a random sampling point collision detection method. The complex three-dimensional models of the collision problem are transformed into simple two-dimensional discrete space optimization problems, and improve the algorithm in real time.
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References
Kimmerle, S.: Collison detection and post-processing for physical cloth simulation:[Dissertation], Tübingen, pp. 28–31 (2005)
Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceeding of 1995 IEEE International Conference on Neural Networks, pp. 1942–1948. IEEE, New York (1995)
Klen, J., Zachmann, G.: Adb-trees: Controlling the error of time-cntical collision detection. In: 8th International Fall Workshop Vision, Modeling, and Visualization (VMV), Germany, pp. 19–21 (2003)
Guy, S., Debunne, G.: Monte-carlo collision detection. Technical Report RR-5136, INRIA, pp. 564–567 (2004)
Raghupathi, L., Grisoni, L., Faure, F., Marchal, D., Cani, M.-P., Chaillou, C.: An intestione surgery simulator: Real-time collision processing and visualization. IEEE Transactions on Visualization and Computer Graphics, 708–718 (2004)
Cohen, J.D., Lin, M.C., Manocha, D., Ponamgi, M.: I-COLLIDE: An interactive and exact collision detection system for large-scale environments. In: Symposium on Interactive 3D Graphics, pp. 189–196 (1995)
Guibas, L.J., Hsu, D., Zhang, L.: H-walk: Hierarchical distance computation for moving convex bodies. In: Oz, W.V., Yannakakis, M. (eds.) Proceedings of ACM Symposium on Computational Geometry, pp. 265–273 (1999)
Kimmerle, S., Nesme, M., Faure, F.: Hierarchy accelerated stochastic collision detection. In: Proceeding of Vision, Modeling, Visualization, pp. 307–314 (2004)
Klen, J., Zachmann, G.: Adb-trees: Controlling the error of time-cntical collision detection. In: 8th International Fall Workshop Vision, Modeling, and Visualization (VMV), Germany, pp. 19–21 (2003)
Wang, T., Li, W., Wang, Y., et al.: Adaptive stochastic collision detection between deformable objects using particle swarm optimization. In: EvoWorkshops: EvolASP, pp. 450–459 (2006)
Guy, S., Debunne, G.: Monte-carlo collision detection. Technical Report RR-5136, INRIA, pp. 564–567 (2004)
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Hu, Td. (2011). Research on Random Collision Detection Algorithm Based on Improved PSO. In: Liu, B., Chai, C. (eds) Information Computing and Applications. ICICA 2011. Lecture Notes in Computer Science, vol 7030. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25255-6_76
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DOI: https://doi.org/10.1007/978-3-642-25255-6_76
Publisher Name: Springer, Berlin, Heidelberg
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