Golden eagle optimizer with double learning strategies for 3D path planning of UAV in power inspection

Jeng-Shyang Pan, Ji-Xiang Lv, Li-Jun Yan, Shao-Wei Weng, Shu-Chuan Chu and Jian-Kai Xue

Mathematics and Computers in Simulation (MATCOM), 2022, vol. 193, issue C, 509-532

Abstract: Unmanned aerial vehicle (UAV) inspection is an indispensable part of power inspection. In the process of power inspection, the UAV needs to obtain an efficient and feasible path in the complex environment. To solve this problem, a Golden eagle optimizer with double learning strategies (GEO-DLS) is proposed. The double learning strategies consist of personal example learning and mirror reflection learning. The personal example learning can enhance the search ability of the Golden eagle optimizer (GEO) and reduce the possibility of the GEO falling into the local optimum. The mirror reflection learning can improve the optimization accuracy of the GEO and accelerate the convergence speed of the GEO. To verify the optimization performance of the algorithm, the proposed GEO-DLS and several other algorithms were tested under the CEC2013 test suite. At the same time, the proposed GEO-DLS and the GEO were analyzed for population diversity and exploration–exploitation​ ratio. Finally, the proposed GEO-DLS is applied to the UAV path planning to generate the initial path, and the cubic B-spline curve is used to smooth the path. These experimental results show that the GEO-DLS has a good performance. The code can be publicly available at: https://www.mathworks.com/matlabcentral/fileexchange/98799-golden-eagle-optimizer-with-double-learning-strategies

Keywords: Unmanned aerial vehicle; Path planning; Personal example learning; Mirror reflection learning; Exploration–exploitation (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475421003967
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:193:y:2022:i:c:p:509-532

DOI: 10.1016/j.matcom.2021.10.032

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().