Research on indoor positioning and navigation method of AGV based on multi-sensor fusion
DOI:
https://doi.org/10.54097/hset.v7i.1060Keywords:
Multi-sensor fusion, AGV, Traceless Kalman filtering, Indoor positioning and navigationAbstract
In comparison with current AGV indoor positioning and navigation methods, the combination of IMU+2D LiDAR is prone to signal loss and cumulative error in indoor, so we propose an AGV indoor navigation and positioning method with multi-sensor fusion of odometer, IMU, LiDAR, and UWB. The model is based on the traceless Kalman filter fusion algorithm, and the UWB positioning provides accurate initial coordinates for the traceless Kalman filter. To verify the feasibility of the method, simulations and experiments are done on MatlabR2020a and experimental platform. The results show that the UWB localization can reduce the accumulated errors brought by IMU, the traceless Kalman filter has good trajectory fitting, the method has good performance in system stability and localization accuracy, and achieves the expected goal.
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H. Liu, X. J. Sheng, H, Zhang and H. Ding, Positioning and Navigation System for Mobile Manipulator Basd on Multisensor Fusion. Mechatronics. Vol. 24 (2018) No. 03, p. 35–40.
S. H. Liao, X. M. Dun and X. Y. Dun, A Localization Method of Indoor Mobile Robot Based on Multi Information Fusion. Machinery & Electronics. (2012) No. 06, p. 64–66.
S. L. Zhang, X. Q. Tan and Q. W. Wu, Indoor mobile robot localization based on multi-sensor fusion technology. Transducer and Microsystem Technologies. Vol. 40 (2021) No. 8, p 53–56.
L. G. Zang, Y. M. Tang, Y. H. Sheng and Z. Z. Wang, Research on Navigation and Positioning System of lntelligent Car Calling Based on UWB. Journal of Chongqing University of Technology. Vol. 35 (2021) No. 7, p 45–52.
Y. C. Liu and Y. M. Gong, Application of Ultra-wideband Positioning Technology based on Kalman FILTER. Software Engineering. Vol. 24 (2021) No. 7, p 24–27.
H. R. Luo and K. C. Liu, High precision positioning system for autopilot based on multi-sensor fusion. E3S Web Conf. Vol. 257 (2021).
W. D. You, F. B. Li, L. Q. Liao and M. L. Huang, Data Fusion of UWB and IMU Based on Unscented Kalman Filter for Indoor Localization of Quadrotor UAV. IEEE Access. Vol. 8 (2020), p 64971–64981.
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