A Fast Collision Detection Algorithm Based on Multi-Agent Particle Swarm Optimization

In this paper, a fast collision detection algorithm based on multi-agent particle swarm optimization (MPSO) is proposed. We use the stochastic method to convert the collision detection problem into a nonlinear optimization problem in the distance mechanism. Combined with the evolution strategy of pa...

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Bibliographic Details
Published in2013 International Conference on Virtual Reality and Visualization pp. 269 - 272
Main Authors Fu Yue-Wen, Liang Jia-Hong, Hu Xiao-Qian, Yang Shan-Liang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2013
Subjects
Algorithm design and analysis
Collision Detection
Geometry
Hierarchical Topological Structure
Multi-agent
Optimization
Particle swarm optimization
Real-time systems
Search problems
Stochastic processes
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Summary:In this paper, a fast collision detection algorithm based on multi-agent particle swarm optimization (MPSO) is proposed. We use the stochastic method to convert the collision detection problem into a nonlinear optimization problem in the distance mechanism. Combined with the evolution strategy of particle swarm optimization and the multi-agent system technology, a multi-agent particle swarm optimization based on the hierarchical topology structure is presented for the problem. The simulation results prove that this algorithm has a good optimal searching performance and it can satisfy the real-time requirement.
DOI:10.1109/ICVRV.2013.52