Abstract
The method of navigation is a very important factor that decides the flexibility and accuracy of the AGV in different operating environments. With each method of navigation, we have different techniques for determining the position and angle of the vehicle. In this research, by fusing data from sensors, the angle, direction and position of the AGV then are estimated by the data of the inertial sensor, encoder and calculated by the Kalman filter algorithm. In addition, the minor inaccuracy in measurement of angle, direction and position are corrected when the AGV passes through the magnetic reference points embedded under the floor based on the virtual paths. The simulation results have proved the accuracy of the proposed algorithm.
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References
Hoang, T.T., Duong, P.M., Van, N.T.T., Viet, D.A., Vinh, T.Q.: Development of an EKF-based localization algorithm using compass sensor and LRF. In: Proceedings of the IEEE 12th International Conference on Control, Automation, Robotics & Vision, pp. 341–346. ICARCV (2012)
Hoang, T.T., Duong, P.M., Van, N.T.T., Viet, D.A., Vinh, T.Q.: Multi-sensor perceptual system for mobile robot and sensor fusion-based localization. In: IEEE 1th International Conference on Control, Automation and Information Sciences, pp.259–264. ICCAIS (2012)
Hoang, T.T., Hiep, D.T., Duong, P.M., Van, N.T.T., Duong, B.G., Vinh, T.Q.: In: Proceedings of the IEEE 8th Conference on Industrial Electronics and Applications, pp.1308–1313. ICIEA (2013)
Klancar, G., Matko, D., Blazic, S.: Mobile robot control on a reference path. In: Proceedings of the 13th Mediterranean Conference on Control and Automation, pp. 1343–1348. Limassol, Cyprus (2005)
Ryck, D.M., Mark, V., Debrouwere, F.: Automated guided vehicle systems, state-of-the-art control algorithms and techniques. J. Manuf. Syst. 54, 152–173 (2020)
Moshayedi, A.J., Roy, A.S., Liao, L.: PID tuning method on AGV (automated guided vehicle) Industrial robot. J. Simul. Anal. Novel Technol. Mech. Eng. 12(4), 53–66 (2020)
Hasan, H.S., Abidin, M.S.Z., Mahmud, M.S.A., Muhamad Said, M.F.: Automated guided vehicle routing: Static, dynamic and free range. J. Int. Eng. Adv. Technol. 8(5C), 1–7 (2019)
Kim, S., Jin, H., Seo, M., Har, D.: Optimal path planning of automated guided vehicle using dijkstra algorithm under dynamic conditions. In: 7th International Conference on Robot Intelligence Technology and Applications (RiTA). IEEE (2019)
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The authors would like to thank Thai Nguyen University of Technology, Viet Nam for the support.
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Thanh, V.C., Quan, N.N.A., Le Thang Dong, T., Hoang, T.T., Nguyen, M.T. (2022). Fusion of Inertial and Magnetic Sensors for Autonomous Vehicle Navigation and Freight in Distinctive Environment. In: Nguyen, D.C., Vu, N.P., Long, B.T., Puta, H., Sattler, KU. (eds) Advances in Engineering Research and Application. ICERA 2021. Lecture Notes in Networks and Systems, vol 366. Springer, Cham. https://doi.org/10.1007/978-3-030-92574-1_45
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DOI: https://doi.org/10.1007/978-3-030-92574-1_45
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