Research on AGV positioning method combined with IMU and UWB




intelligent storage system, extended Kalman filter, AGV, data fusion positioning, inertial navigation


Aiming at the problem that automated guided vehicle (AGV) is difficult to locate accurately due to the influence of environment and time drift when it works in the indoor intelligent storage system. In this paper, an extended Kalman filtering (EKF) framework is designed. In order to make full use of the original ranging values of ultra wideband (UWB) and inertial measurement unit (IMU), the framework realizes the fusion positioning between UWB module and IMU module in a tight coupling manner, so as to ensure that the system can still work when the available base station signal is inaccurate. Firstly, for the problem that the traditional UWB positioning method is easily affected by the non-line of sight (NLOS) error in-doors, the calculated positioning coordinate value is unstable. With the help of different NLOS probability distribution curves of different obstacles, the weighted least square method is applied to the UWB positioning method to determine the positioning coordinate value of UWB, which improves the sudden change of AGV positioning coordinate in the static environment. Then the data fusion algorithm is optimized, and the error value of IMU and UWB coordinate is taken as the observation value of EKF, which reduces the influence of cumulative error on IMU positioning results, provides the global optimal estimation of the system optimal state, and improves the fusion positioning accuracy. Finally, the measured data of UWB and IMU systems in indoor complex environment are simulated in MATLAB. The experimental results show that when NLOS signal seriously affects the positioning effect, the UWB and IMU combined positioning system can provide more reliable positioning results than the single IMU positioning system. It improves the positioning accuracy of AGV and provides a new idea for indoor positioning mode.


Ai, H., Li, Y. (2017) Weighted centroid location algorithm based on RSSI ranging filter optimization. Journal of the Computer Engineering and Design,3811(10), 2631-2635.

Cao, B., Wang, S. B., Ge, S. R. (2022) Research on positioning strategy and technology of shearer end based on ultra wideband system. Journal of the Coal Science and Technology, 50(03), 257-266.

Ding, L., Zhang, Y., Yin, S. C., et al. (2018) Discussion on the development status and trends of my country's logistics and storage industry. Journal of the Hoisting and Conveying Machinery, (4), 69-71.

Jiang, W., Cao, Z, J., Lu, D, B., et al. (2021) UWB enhanced integrated navigation method under GNSS constraints. Journal of the Railway Transaction, 43(03), 111-119.

Jiang, W., Cao, Z. J., Lu, D. B., et al. (2021) UWB enhanced integrated navigation method under GNSS constraints. Journal of the Railway Transaction, 43(03), 111-119.

Jiang, W., Li, Y., Rico, Z., et al. (2017) Seamless Indoor-outdoor Navigation based on GNSS, INS and Terrestrial Ranging Techniques. Journal of the Navigation, 70(6), 1183-1204.

Jiang, X., Zhang, H., Wei, W., et al.(2012) NLOS error mitigation with information fusion algorithm for UWB ranging systems. Journal of the China Universities of Posts and Telecommunications. 19(2), 22-29.

Li, K. P., Liu, T. B., He, B. Q., et al. (2022) Research on AGV path planning and scheduling in "goods to people" picking system. Journal of the Chinese Management Science, 30(04), 240-251.

Li, S., Yuan, Z, G., Wang, C., et al. (2018) A survey of swarm intelligence algorithms for optimizing support vector machine parameters. Journal of the Intelligent Systems, 13(1), 70-84.

Liang, Y., Zhang, Q, D., Zhao, Ning, et al. (2021) Indoor positioning method based on fusion of UWB and inertial navigation. Journal of the Infrared and Laser Engineering, 50(09), 293-306.

Liu, Q. L., Wang, Z. P., Zhou, W. M., et al. (2021) An improved indoor location method based on multi-source information fusion. Journal of the Telecommunication Engineering, 61(12), 1526-1533.

Michlowicz, E. (2021) Logistics engineering and industry 4.0 and digital factory. Journal of the Archives of Transport, 57(01), 59-72. DOI:

Ning, Y. S., Li, Q. S., Lu, P. H., et al. (2020) Collaborative optimization algorithm of intelligent storage location planning and AGV path planning. Journal of the Software, 31(09), 2770-2784.

Oulose, A., Eyobu, S., Han, D. S., et al. (2019) An indoor position estimation algorithm using smartphone IMU sensor data. Journal of the IEEE Access, 7(8), 11165-11177.

San, M., Cortes, A., (2020) Precise positioning of autonomous vehicles combining UWB ranging estimations with on-board sensors. Journal of the Navigation Electronics, 9(8), 1238.

Uradzinski, M., Guo, H., Liu, X., et al. (2017) Advanced indoor positioning using Zigbee wireless technology. Journal of the Wireless Personal Communications, 97(67), 6509-6518.

Wang, C. Q., Feng, D. Q., He, C. L., et al. (2019) Research on enhanced asymmetric bilateral bidirectional ranging algorithm based on UWB. Journal of the Nanchang Aeronautical University, 33(01), 66-73.

Xu, Y. L., Zheng, Z. W., Sun, L., et al. (2018) Multi sensor fusion PDR location method based on Neural Network. Journal of the Sensing Technology, 31(04), 579-587.

Yang, G., Zhu, S. L., Li, Qiang., et al. (2021) Firefighter indoor location and NLOS detection algorithm integrating UWB and IMU. Journal of the Computer Engineering, 47(09), 153-161.

Yin, K. Y., Liang, W., Yang, J. B., et al. (2021) An efficient UWB and IMU fusion localization algorithm in power operation scenarios. Journal of the China Power, 54(08), 83-90.

Yu, K., Wen, K., (2019) A novel NLOS mitigation algorithm for UWB localization in harsh indoor environments. Journal of the IEEE Transactions on Vehicular Technology, 68(1), 686-699.

Zhang, D. C., Wei, G. L., Tian, X., et al. (2019) Dynamic updating channel model positioning system based on particle filter in NLOS environment. Journal of the Small Microcomputer System, 40(12), 2608-2613.

Zhang, Y. D., Tian, L., Li, M. Q., et al.(2017) Application research and demonstration of intelligent patrol robot system in thermal power industry. Journal of the China Power, 50(10), 1-7.

Zhou, J., Wei, G. L., Tian, X., et al. (2021) A new indoor location algorithm integrating UWB and IMU data. Journal of the Small Microcomputer System, 42(08), 1741-1746.






Original articles

How to Cite

Qiu, J., Zhang, Y., Tang, M., Ma, P., & Ran, J. (2022). Research on AGV positioning method combined with IMU and UWB. Archives of Transport, 64(4), 107-117.


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