Three-Dimensional Route Planning Based on the Beetle Swarm Optimization Algorithm

Swarm intelligence algorithms have better intelligence and adaptation compared with the traditional route planning method. A three-dimensional route planning method based on the beetle swarm optimization (BSO) algorithm was proposed. The iterative updating strategy of the BSO algorithm cooperated wi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE access 2019, Vol.7, p.117804-117813
Hauptverfasser: Mu, Yizhuo, Li, Baoke, An, Dong, Wei, Yaoguang
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Swarm intelligence algorithms have better intelligence and adaptation compared with the traditional route planning method. A three-dimensional route planning method based on the beetle swarm optimization (BSO) algorithm was proposed. The iterative updating strategy of the BSO algorithm cooperated with the search mechanism of the beetle monomer and the updating strategy of the particle swarm optimization (PSO) algorithm, thus accelerating iterative convergence and decreasing the probability of trapping in the local optimal solution of the algorithm. The practical engineering problem of three-dimensional route planning was addressed by processing uneven ground barriers using the penalty function, and a smooth route is gained from cubic spline interpolation. In this study, a three-dimensional environmental model was constructed by using actual elevation data from the USGS/NASA SRTM, and a simulation experiment of three-dimensional route planning was performed using the proposed method. The proposed method was compared with other algorithms. Experimental results demonstrated that when the iteration time was set to 50, the route planning length based on BSO algorithm was about 90% of the route planning based on the PSO algorithm. Moreover, the proposed route planning method had high convergence rate and stable convergence result and is applicable to three-dimensional route planning.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2935835