THREE-PHASE QUBITS-BASED QUANTUM ANT COLONY OPTIMIZATION ALGORITHM FOR PATH PLANNING OF AUTOMATED GUIDED VEHICLES

Junjun Li, Bowei Xu, Yongsheng Yang, and Huafeng Wu

Keywords

Quantum ant colony optimization, three-phase qubits, artificial potential field, automated guided vehicles, path planning

Abstract

In this work, a novel quantum ant colony optimization for the path planning of automated guided vehicles (AGVs) based on three- phase qubits is presented. First, three-phase qubits, which can achieve a trade-off between the searching accuracy and speed, are utilized. 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 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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