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| A New Parallel Collision Detection Algorithm Based on Particle Swarm Optimization |
| Yumei Xiong, Chao Li, Yimin Chen |
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Abstract A new parallel collision detection algorithm based on Particle Swarm
Optimization (PSO) is proposed in the paper. The collision detection
problem is transformed to the optimization problems of the space
formed by the number of characteristics of the two models. Using the
intelligent search features of the PSO algorithm, the search process
of the local minimum characteristics is completed during collision
detection. The optimization model is fully parallel by dividing
polyhedron algorithm. The parallel method improves the detection
speed for further step. The test results show the collision
detection algorithm based on PSO can improve time efficiency. With
the application of parallel technology, the detection speed can be
further improved by adjusting the number of computer nodes.
DOI: 10.12733/jics20101677
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