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Proceedings Paper

Adaptive PSO using random inertia weight and its application in UAV path planning
Author(s): Hongguo Zhu; Changwen Zheng; Xiaohui Hu; Xiang Li
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Paper Abstract

A novel particle swarm optimization algorithm, called APSO_RW is presented. Random inertia weight improves its global optimization performance and an adaptive reinitialize mechanism is used when the global best particle is detected to be trapped. The new algorithm is tested on a set of benchmark functions and experimental results show its efficiency. APSO_RW is later applied in UAV (Unmanned Aerial Vehicle) path planning.

Paper Details

Date Published: 13 October 2008
PDF: 5 pages
Proc. SPIE 7128, Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment, 712814 (13 October 2008); doi: 10.1117/12.806636
Show Author Affiliations
Hongguo Zhu, Institute of Software (China)
National Univ. of Defense Technology (China)
Changwen Zheng, Institute of Software (China)
Xiaohui Hu, Institute of Software (China)
Xiang Li, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 7128:
Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment

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