An Improved PSO-GWO Algorithm With Chaos and Adaptive Inertial Weight for Robot Path Planning

The traditional particle swarm optimization (PSO) path planning algorithm represents each particle as a path and evolves the particles to find an optimal path. However, there are problems in premature convergence, poor global search ability, and to the ease in which particles fall into the local opt...

Descripción completa

Detalles Bibliográficos
Autores principales: Cheng, Xuezhen, Li, Jiming, Zheng, Caiyun, Zhang, Jianhui, Zhao, Meng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8602895/
https://www.ncbi.nlm.nih.gov/pubmed/34803648
http://dx.doi.org/10.3389/fnbot.2021.770361

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8602895/
https://www.ncbi.nlm.nih.gov/pubmed/34803648
http://dx.doi.org/10.3389/fnbot.2021.770361

Ejemplares similares