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Dynamics model and simulation of outdoor AGV obstacle crossing without 3D model

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Abstract

In this study, an outdoor automated guided vehicle (AGV) with an absorbent vibration system was designed, and a 7-degrees of freedom (DOF) model was established for this system. We built a simulation model in Simulink software that serves as the 7-DOF model. The three indicators for evaluating the stability of the AGV are simulated and analyzed in the simulation model when one side of the AGV crosses a sloping obstacle. A vibration absorptive property experiment of the AGV was performed, and the average maximum displacement of the AGV sprung mass was 13.42 mm. The maximum predicted amplitude of sprung mass in the Simulink simulation model is 12.8 mm, and its prediction error is about 4.6%. The prediction accuracy of the Simulink model is higher than that of the Adams simulation method. According to the efficiency comparison experiment of the AGV obstacle crossing simulation method, the obstacle crossing simulation method based on Simulink designed in this paper saves about 28% of the working time of the designer compared with the traditional Adams simulation method, which provides a new idea for the simulation method of outdoor AGV obstacle crossing before the 3D model is established.

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References

  1. Sabattini L, Aikio M, Beinschob P et al (2017) The PAN-Robots Project: advanced automated guided vehicle systems for industrial logistics. IEEE Robot Autom Mag:1–1

  2. Pham TN, Ton T (2020) Design and control of automated guided vehicle. Appl Mech Mater 902:33–42

    Article  Google Scholar 

  3. Ryck VM, Debrouwere F (2020) Automated guided vehicle systems, state-of-the-art control algorithms and techniques. J Manuf Syst 54(1):152–173

    Article  Google Scholar 

  4. Xue DL, Jie-Ying XU, Xie SH et al (2019) Application of AGV (automated guided vehicle) in cold-rolling grinding roll shop. Heavy Mach

  5. Qu S, Yao P, Gong Y (2021) Modelling and grinding characteristics of unidirectional C–SiCs. Ceram Int

  6. Qu S, Yao P, Gong Y (2022) Environmentally friendly grinding of C/SiCs using carbon nanofluid minimum quantity lubrication technology. J Clean Prod

  7. F Tong,Xu. A high precision ultrasonic docking system used for automatic guided vehicle. Sensors Actuators A Phys,2005,118(2):183-189.

    Article  CAS  Google Scholar 

  8. Ruiz V,Sierra G. Simulation tool for tybrid AGVs based on ICE-61131. IEEE Lat Am Trans,2021, 20(2):317-325.

    Article  Google Scholar 

  9. Ahmadian M (2017) Magneto-rheological suspensions for improving ground vehicle’s ride comfort,stability,and handling. Veh Syst Dyn 55(10):1618–1642

    Article  ADS  MathSciNet  Google Scholar 

  10. Li-hui Z, Yue-zhong Z (2020) Simulink-based modeling and simulation of 1/4 vehicle suspension. Times Automot 20:148–149

    Google Scholar 

  11. Abdi B, Mirzaei M, Mojed GR (2017) A new approach to optimal control of nonlinear vehicle suspension system with input constraint. J Vib Control. https://doi.org/10.1177/1077546317704598

  12. Roebuck R, Cebon D (2008) Implementation of semi-active damping on a tri-axle heavy-vehicle suspension. Proc Inst Mech Eng D J Automob Eng 222(D12):2353–2372

    Article  Google Scholar 

  13. Zhen-feng W (2018) Research on state estimation and control of vehicle suspension system considering vertical and lateral motion characteristics. Beijing University of Technology

    Google Scholar 

  14. Amed G,Hiza S. Trouser tearing of a model natural rubber tire belt vulcanizate. Part 2:A Brief note on the effect of cure time. Rubber Chem Technol, 2010, 83(2):213-225.

    Article  Google Scholar 

  15. Liu-bo, Guo-jun W, Shao-feng L (2019) Effect of obstacle shape on vehicle impact smoothness. J Mil Traffic Acad 21(06):86–91

    Google Scholar 

  16. Besselink I,Schmeitz A,Pacejka H. An improved Magic Formula/Swift tyre model that can handle inflation pressure changes. Veh Syst Dyn,2010,48(3):337-352.

    Article  ADS  Google Scholar 

  17. Yim S (2016) Coordinated control of ESC and AFS with adaptive algorithms. Int J Automot Technol 18(2):271–277

    Article  Google Scholar 

  18. Feledy C, Luttenberger M S. A state-of-the-art map of the AGVS technology and a guideline for how and where to use it. 2017.

  19. Oyekanlu EA, Smith AC, Thomas WP et al (2020) A review of recent advances in automated guided vehicle technologies: integration challenges and research areas for 5G-based smart manufacturing applications. IEEE Access 8:202312–202353

    Article  Google Scholar 

  20. Ivanov D, Dolgui A, Sokolov B et al (2016) A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0. Int J Prod Res 54(1-2):386–402

    Article  Google Scholar 

  21. Vis I (2006) Survey of research in the design and control of automated guided vehicle systems. Oper Res

  22. Guan W, Huang L, Wen S et al (2021) Robot localization and navigation using visible light positioning and SLAM fusion. J Lightwave Technol 39

  23. Yu X, Fan Z, Wan H et al (2019) Positioning, navigation, and book accessing/returning in an autonomous library robot using integrated binocular vision and QR code identification systems. Sensors 19(4)

  24. Um I, Cheon H, Lee H (2009) The simulation design and analysis of a Flexible Manufacturing System with Automated Guided Vehicle System. J Manuf Syst 28(4):115–122

    Article  Google Scholar 

  25. Riehle T H, Anderson S M, Lichter P A, et al. Indoor magnetic navigation for the blind. Engineering in Medicine & Biology Society. IEEE, 2012:1972-1975.

  26. Lu S, Xu C, Zhong RY et al (2017) A RFID-enabled positioning system in automated guided vehicle for smart factories. J Manuf Syst 44:179–190

    Article  Google Scholar 

  27. Kuznetsov AG, Molchanov AV, Chirkin MV et al (2015) Precise laser gyroscope for autonomous inertial navigation. Quantum Electron 45(1):78–88

    Article  ADS  CAS  Google Scholar 

  28. Zhang H, Zhang C, Wei Y, et al. Localization and navigation using QR code for mobile robot in indoor environment. IEEE, 2015.

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Funding

This project is supported by the National Natural Science Foundation of China (Grant No. 51775101).

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Contributions

Yingbo Zhao: contributed to the conception of the study, data analyses, and wrote the manuscript; Shichao Xiu: contributed to the conception of the study; Yuan Hong: contributed significantly to analysis and manuscript preparation; Xinyu Bu: performed the experiment.

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Correspondence to Shi-chao Xiu.

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Zhao, Yb., Xiu, Sc., Hong, Y. et al. Dynamics model and simulation of outdoor AGV obstacle crossing without 3D model. Int J Adv Manuf Technol 131, 2615–2624 (2024). https://doi.org/10.1007/s00170-023-12056-y

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  • DOI: https://doi.org/10.1007/s00170-023-12056-y

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