THREE-PHASE QUBITS-BASED QUANTUM ANT COLONY OPTIMISATION ALGORITHM FOR PATH PLANNING OF AGVs

Li Junjun, Xu Bowei, Yang Yongsheng, Wu Huafeng

Keywords

Quantum Ant Colony Optimisation, Three-phase Qubits, Artificial Potential Field, Automated Guided

Abstract

In this work, a novel quantum ant colony optimisation for the path planning of automated guided vehicles (AGVs) based on three-phase qubits is presented. First, multi-phase qubits, in which the best solution corresponds to multiple best angles, are analysed. Subsequently, three-phase qubits, which can achieve a trade-off between the searching accuracy and speed, are utilised in quantum ant colony optimisation. Second, an artificial potential field for road networks with discrete links and nodes is defined to avoid conflicts among AGVs. Attractive and repulsive forces are employed in the state transition rule to guide AGVs to their destinations and maintain the space–time distances among them. Finally, two typical working modes—operation line and operation parallel—are simulated for the path planning of AGVs at an automated container terminal. The simulation results illustrate the superiority of the proposed algorithm.

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