Hybrid collision detection algorithm based on particle conversion and bounding box

被引：0

作者：

Tang Y. ^{[1
]}

Hou J. ^{[1
]}

Wu T. ^{[1
]}

Gong S. ^{[1
]}

Zhang J. ^{[1
]}

Zhong L. ^{[1
]}

机构：

[1] School of Information Science and Technology, Southwest Jiaotong University, Chengdu

来源：

Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University | 2018年 / 39卷 / 10期

关键词：

Binary tree; Collision detection; OBB hierarchical bounding box; Particle conversion; Particle reduction; Regional center;

D O I：

10.11990/jheu.201701036

中图分类号：

学科分类号：

摘要：

To improve the efficiency of collision detection, this paper presents a collision detection algorithm based on particle conversion and bounding box. The algorithm first makes use of the binary tree and regional center to construct an oriented bounding box (OBB) for all objects in space, then expresses objects separated by a certain distance as a physical particle. The outermost OBB of the object was considered as a dot in a three-dimensional space, so as to calculate the distance between two objects. This distance was determined using the result of dot calculation and distance of reduction, so that the dot that did not pass the test was not detected again, while the dot that passed the validation was reduced. Finally, the OBB intersection test was carried out on the reduced bounding box. The results showed that the proposed algorithm can effectively improve collision detection efficiency compared with its predecessor algorithm, and can further reduce the time and cost of the increased space, especially for the complicated environment where a large number of objects exist in the space. © 2018, Editorial Department of Journal of HEU. All right reserved.

引用

页码：1695 / 1701

页数：6

共 15 条

[1] Yu L., Wang T., Song H., Et al., An optimization algorithm of collision detection applied to virtual surgery, Journal of Harbin Engineering University, 35, 9, pp. 1164-1170, (2014)
[2] Wong S.K., Lin W.C., Huang C.H., Et al., Radial view based culling for continuous self-collision detection of skeletal models, ACM Transactions on Graphics, 32, 4, (2013)
[3] Schvartzman S.C., Perez A.G., Otaduy M.A., Star-contours for efficient hierarchical self-collision detection, ACM Transactions on Graphics, 29, 4, (2010)
[4] Tang M., Manocha D., Yoon S.E., Et al., VolCCD: fast continuous collision culling between deforming volume meshes, ACM Transactions on Graphics, 30, 5, (2011)
[5] Tang M., Manocha D., Kim Y.J., Hierarchical and controlled advancement for continuous collision detection of rigid and articulated models, IEEE Transactions on Visualization and Computer Graphics, 20, 5, pp. 755-766, (2014)
[6] Ouyang F., Zhang T., Octree-based spherical hierarchical model for collision detection, Proceedings of the 10th World Congress on Intelligent Control and Automation, pp. 3870-3875, (2012)
[7] He L., Ortiz R., Enquobahrie A., Et al., Interactive continuous collision detection for topology changing models using dynamic clustering, Proceedings of the 19th Symposium on Interactive 3D Graphics and Games, pp. 47-54, (2015)
[8] Pabst S., Koch A., Stasser W., Fast and scalable CPU/GPU collision detection for rigid and deformable surfaces, Computer Graphics Forum, 29, 5, pp. 1605-1612, (2010)
[9] Wang H., Defending continuous collision detection against errors, ACM Transactions on Graphics, 33, 4, (2014)
[10] Brochu T., Edwards E., Bridson R., Efficient geometrically exact continuous collision detection, ACM Transactions on Graphics, 31, 4, (2012)

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