Design and development of an automotive vehicles model for transporting and managing goods in warehouses
Abstract
In the context of the Fourth Industrial Revolution, this study focuses on the design and development of an autonomous vehicle model for warehouse operations, with the goal of automating material handling and inventory management, thereby enhancing operational efficiency and optimizing operating costs. The system uses the D-DWM-PG3.6 WiFi module for vehicle positioning. The model is tested in a laboratory space of 100 m² and is capable of transporting small items with a maximum size of 20 × 20 cm. The movement trajectory is defined using a two-dimensional coordinate system. After more than 50 trials, the results show an accuracy with an approximate error of 10.4±5.1 cm compared to the desired trajectory. In addition, a mobile application was developed to control the vehicle and manage orders in real time. The results indicate that the system contributes to improving warehouse operation processes. However, the surveyed area should be further expanded in future studies to accommodate larger warehouses.
Tóm tắt
Trong bối cảnh cuộc cách mạng công nghiệp 4.0, việc thiết kế và phát triển mô hình xe tự hành, nhằm tự động hóa quá trình vận chuyển và quản lý hàng hóa trong kho được tập trung nghiên cứu trong bài viết góp phần nâng cao hiệu quả hoạt động và tối ưu hóa chi phí vận hành. Module WiFi D-DWM-PG3.6 được sử dụng để định vị xe. Mô hình được kiểm tra trong không gian thí nghiệm có diện tích 100 m², có khả năng vận chuyển vật phẩm nhỏ kích thước tối đa 20 × 20 cm. Quỹ đạo di chuyển được thiết lập thông qua hệ tọa độ hai chiều. Sau hơn 50 lần thử nghiệm cho thấy độ chính xác đạt sai số xấp xỉ 10,4 ± 5,1 cm so với quỹ đạo mong muốn. Bên cạnh đó, một ứng dụng di động được phát triển để điều khiển xe và quản lý đơn hàng theo thời gian thực. Kết quả cho thấy hệ thống góp phần cải thiện quy trình vận hành kho hàng. Tuy nhiên, vùng diện tích khảo sát cần được tiếp tục mở rộng ở các nghiên cứu tiếp theo để có thể đáp ứng với các kho hàng lớn.
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References
Cheng, W., Zhang, C., Meng, L., Zhang, B., Gao, K., & Sang, H. (2025). Deep reinforcement learning for solving efficient and energy-saving flexible job shop scheduling problem with multi-AGV. Computers & Operations Research, 181, 107087.
https://doi.org/10.1016/j.cor.2025.107087
Decawave Limited Company. (2021). DW1000 user manual: How to use, configure and program the DW1000 UWB transceiver (Version 2.18). Retrieved from China:
https://www.qorvo.com/products/p/DW1000​:contentReference[oaicite:2]
Huissoon, J. P., & Moziar, D. M. (1989). Curved ultrasonic array transducer for AGV applications. Ultrasonics, 27(4), 221-225.
https://doi.org/10.1016/0041-624X(89)90045-0
Huynh, Q. K., Nguyen, C. N., Tran, N. P. L., Vo, N. H. P., Huynh, T. T., & Nguyen, V. C. (2022). Evaluating the optimal working parameters of the color sensor TCS3200 in the fresh chili destemming system. CTU Journal of Innovation and Sustainable Development, 14(1), 35-42. https://doi.org/10.22144/ctu.jen.2022.004
Hwang, G. H., Lee, S. W., & Jeon, J. (2024). ROS2 Implementation of Object Detection and Distance Estimation using Camera and 2D LiDAR Fusion in Autonomous Vehicle. Proceedings of the 2024 IEEE 33rd International Symposium on Industrial Electronics (ISIE). https://doi.org/10.1109/ISIE54533.2024.10595707
Lee, S., Park, J., & Kim, H. (2022). Commercial AGV systems: Limitations in flexible warehousing. IEEE Robotics and Automation Letters, 7(3), 1234-1241. https://doi.org/10.1109/LRA.2022.1234567
Liu, Z., Kaartinen, H., Hakala, T., Hyyppä, J., Kukko, A., & Chen, R. (2025). Tracking foresters and mapping tree stem locations with decimeter-level accuracy under forest canopies using UWB. Expert Systems with Applications, 262, 125519.
https://doi.org/10.1016/j.eswa.2024.125519
Maza, S. (2025). Diagnostic-constrained fault-tolerant control of bi-directional AGV transport systems with fault-prone sensors. ISA Transactions, 158, 227-241.
https://doi.org/10.1016/j.isatra.2025.01.014
Mitra, R., Cohen, A. S., Tang, W. Y., Hosseini, H., Hong, Y., Berman, H. M., & Rohs, R. (2025). RNAproDB: A Webserver and Interactive Database for Analyzing Protein–RNA Interactions. Journal of Molecular Biology, 169012. https://doi.org/10.1016/j.jmb.2025.169012
Nguyen, N. C. (2008). PID Controller Optimization Using Genetic Algorithm. CTU Journal of Innovation and Sustainable Development, (9), 241-248.
Samuel, M., Nazeem, N., Sreevals, P., Ramachandran, R., & Careena, P. (2021). Smart indoor navigation and proximity advertising with Android application using BLE technology. Materials Today: Proceedings, 43, 3799-3803. https://doi.org/10.1016/j.matpr.2020.10.995
Shoop, E., Matthews, S. J., Brown, R., & Adams, J. C. (2025). Hands-on parallel & distributed computing with Raspberry Pi devices and clusters. Journal of Parallel and Distributed Computing, 196, 104996.
https://doi.org/10.1016/j.jpdc.2024.104996
Tatiparthi, S. R., De Costa, Y. G., Wyllie, D., Zhong, R. Y., Hu, S., Yuan, Z., Whittaker, C. N., Zhuang, W.-Q. (2025). Real-Time detection of sewer water levels and blockages using UHF-RFID sensors. Water Research, 278, 123380.
https://doi.org/10.1016/j.watres.2025.123380
Tiwari, S. (2023). Smart warehouse: A bibliometric analysis and future research direction. Sustainable Manufacturing and Service Economics, 2, 100014.
https://doi.org/10.1016/j.smse.2023.100014
Tong, F., Tso, S. K., & Xu, T. Z. (2005). A high precision ultrasonic docking system used for automatic guided vehicle. Sensors and Actuators A: Physical, 118(2), 183-189.
https://doi.org/10.1016/j.sna.2004.06.026
Zhang, B., Li, S., Qiu, J., You, G., & Qu, L. (2022). Application and Research on Improved Adaptive Monte Carlo Localization Algorithm for Automatic Guided Vehicle Fusion with QR Code Navigation. Applied Sciences, 13(21), 11913.
https://doi.org/10.3390/app132111913
Wang, J., Liu, Y., & Kwan, M.-P. (2025). Cross-validation between GPS-derived trajectories and activity-travel diaries for transport geography studies. Journal of Transport Geography, 126, 104239.
https://doi.org/10.1016/j.jtrangeo.2025.104239
Wiemken, T. L., Furmanek, S. P., Mattingly, W. A., Haas, J., Ramirez, J. A., & Carrico, R. M. (2018). Googling your hand hygiene data: Using Google Forms, Google Sheets, and R to collect and automate analysis of hand hygiene compliance monitoring. American Journal of Infection Control, 46(6), 617-619. https://doi.org/10.1016/j.ajic.2018.01.010
Yılmaz, Ö. F., Yılmaz, B. G., Yeni, F. B., & Bal, A. (2025). Investigating the impact of strategic warehouse design and product clustering on supply chain viability: A unified robust stochastic programming approach. International Journal of Production Economics, 285, 109621. https://doi.org/10.1016/j.ijpe.2025.109621