Agv path selection method considering communication information

Abstract Recent advances in IoT technology have accelerated the realization of smart factories. Within these environments, automated guided vehicles (AGVs) play an important role in material transportation. However, as the number of wireless devices operating simultaneously within a factory increases, maintaining stable communication among mobile AGVs becomes a major challenge due to signal fluctuations, interference, and fluctuations in communication demand. To address this challenge, this paper proposes an adaptive AGV communication framework that combines a wireless unit (RU) selection method and a routing algorithm that consider both wireless conditions and network load. Specifically, we introduce three RU selection methods: the Maximum SNR RU Selection Method (MSS), the Least-Connected RU Selection Method (LCS), and the Joint Distance and Load RU Selection Method (DLS). We also introduce two path determination methods: the Shortest Path Determination Method (SPD) and the proposed Utilization-Aware Path Determination Method (UPD) that dynamically avoids congested RUs. Simulation results for random task movement scenarios and primary task movement scenarios show that the DLS (UPD) method achieves improved average throughput compared to the conventional MSS-SPD method. Furthermore, the proposed method maintains communication stability even when conventional AGVs coexist in the same environment, demonstrating its effectiveness for dynamic wireless communication management in industrial networks.