Research on random collision detection algorithm based on improved PSO

0Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

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. © 2011 Springer-Verlag.

Cite

CITATION STYLE

APA

Hu, T. D. (2011). Research on random collision detection algorithm based on improved PSO. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7030 LNCS, pp. 602–609). https://doi.org/10.1007/978-3-642-25255-6_76

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free