Design of an Intelligent AGV System Based on Dynamic Navigation and Warehouse Visualization

Can Liang; Liangxu Sun; Shuaiye Luo; Ruihao Wu; Xingnuo Liu

doi:10.54097/sx8bd911

Authors

Can Liang
Liangxu Sun
Shuaiye Luo
Ruihao Wu
Xingnuo Liu

DOI:

https://doi.org/10.54097/sx8bd911

Keywords:

AGV Navigation, Digital Twin, Dynamic Path Planning, Three.js, Fault-tolerant Mechanism

Abstract

Focusing on the core role of intelligent AGV systems in smart warehousing, this paper proposes a hybrid navigation architecture integrating magnetic guidance and visual SLAM, combined with visualization technology to achieve full-process monitoring of warehouse operations. The system enhances environmental adaptability through multi-source sensor data fusion (magnetic guidance accuracy: ±1 cm, visual SLAM dynamic correction). Efficient obstacle avoidance is realized via A* global path planning and the Dynamic Window Approach (DWA). A digital twin visualization platform is constructed using the Three.js engine, supporting real-time AGV trajectory rendering and anomaly warnings. The design adopts a distributed fault-tolerant mechanism (hardware redundancy + software degradation) to ensure system reliability, providing scalable technical references for warehouse automation upgrades.

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References

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