To read this content please select one of the options below:

Quantum-entanglement pigeon-inspired optimization for unmanned aerial vehicle path planning

Siqi Li (School of Automation Science and Electrical Engineering, Beihang University, Beijing, China)
Yimin Deng (School of Automation Science and Electrical Engineering, Beihang University, Beijing, China)

Aircraft Engineering and Aerospace Technology

ISSN: 0002-2667

Article publication date: 15 November 2018

Issue publication date: 30 January 2019

209

Abstract

Purpose

The purpose of this paper is to propose a new algorithm for independent navigation of unmanned aerial vehicle path planning with fast and stable performance, which is based on pigeon-inspired optimization (PIO) and quantum entanglement (QE) theory.

Design/methodology/approach

A biomimetic swarm intelligent optimization of PIO is inspired by the natural behavior of homing pigeons. In this paper, the model of QEPIO is devised according to the merging optimization of basic PIO algorithm and dynamics of QE in a two-qubit XXZ Heisenberg System.

Findings

Comparative experimental results with genetic algorithm, particle swarm optimization and traditional PIO algorithm are given to show the convergence velocity and robustness of our proposed QEPIO algorithm.

Practical implications

The QEPIO algorithm hold broad adoption prospects because of no reliance on INS, both on military affairs and market place.

Originality/value

This research is adopted to solve path planning problems with a new aspect of quantum effect applied in parameters designing for the model with the respective of unmanned aerial vehicle path planning.

Keywords

Citation

Li, S. and Deng, Y. (2020), "Quantum-entanglement pigeon-inspired optimization for unmanned aerial vehicle path planning", Aircraft Engineering and Aerospace Technology, Vol. 91 No. 1, pp. 171-181. https://doi.org/10.1108/AEAT-03-2018-0107

Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

Related articles