Adaptive PSO using random inertia weight and its application in UAV path planning

Hongguo Zhu; Changwen Zheng; Xiaohui Hu; Xiang Li

doi:10.1117/12.806636

13 October 2008 Adaptive PSO using random inertia weight and its application in UAV path planning

Hongguo Zhu, Changwen Zheng, Xiaohui Hu, Xiang Li

Proceedings Volume 7128, Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment; 712814 (2008) https://doi.org/10.1117/12.806636
Event: Seventh International Symposium on Instrumentation and Control Technology, 2008, Beijing, China

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.

Citation Download Citation

Hongguo Zhu, Changwen Zheng, Xiaohui Hu, and Xiang Li "Adaptive PSO using random inertia weight and its application in UAV path planning", Proc. SPIE 7128, Seventh International Symposium on Instrumentation and Control Technology: Measurement Theory and Systems and Aeronautical Equipment, 712814 (13 October 2008); https://doi.org/10.1117/12.806636

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