Fuzzy Arm Controller for Critical Slope Crossing and Quasi-Rotational Strategy for Intense Bump Crossing

  • Mohamadreza Satvati
  • Masoud Masih-Tehrani
  • Abdollah Amirkhani Iran University of Science and Technology
  • Mohammad Parsa Karimi
Keywords: Tracked vehicles, Tip-over, Critical slope, fuzzy sets, Crossing bump


Research shows that most of the damage to off-road vehicles is due to a lack of balance in critical situations. This paper is studying the impact of the arm on tracked vehicle trafficability on critical slopes. The position and weight of the arm have a direct effect on the position and location of the tracked vehicle's center of mass. The neural network is used to find the function between the position of the vehicle's center of mass and the maximum slope traverse ability. The neural network is trained using experimental data. In this study, while investigating the effect of arm position on vehicle trafficability, a fuzzy control system is designed to maintain a tracked vehicle balance at a critical slope. This controller prevents the tracked vehicle from tip-over on the critical slope. Based on vehicle speed control, a controlling system is also designed for crossing the bump. A quasi-rotational motion for a tracked vehicle, makes it possible to cross the bump which it cannot pass in normal condition. The small tracked vehicle is equipped for trafficability experiments. The pitch angle is compared and validated between simulations and experiments.


[1] J. Y. Wong, Terramechanics and off-road vehicle engineering: terrain behaviour, off-road vehicle performance and design, Butterworth-Heinemann, 2009.
[2] R. Raper, A. Bailey, E. Burt, … T. W.-J. of, and undefined 1995, “The effects of reduced inflation pressure on soil-tire interface stresses and soil strength,” Elsevier.
[3] H. Taghavifar and A. Mardani, “Investigating the effect of velocity, inflation pressure, and vertical load on rolling resistance of a radial ply tire,” J. Terramechanics, vol. 50, no. 2, pp. 99–106, Apr. 2013.
[4] M. Kise and Q. Zhang, “Sensor-in-the-loop tractor stability control: Look-ahead attitude prediction and field tests,” Comput. Electron. Agric., vol. 52, no. 1–2, pp. 107–118, Jun. 2006.
[5] D. Rey, E. P.-P. of the 1997 IEEE, and undefined 1997, “Online automatic tipover prevention for mobile manipulators,” ieeexplore.ieee.org.
[6] S. Dubowsky and E. E. Vance, “Planning mobile manipulator motions considering vehicle dynamic tability constraints,” in Proceedings, 1989 International Conference on Robotics and Automation, pp. 1271–1276.
[7] A. Ghasempoor and N. Sepehri, “A measure of machine stability for moving base manipulators,” in Proceedings of 1995 IEEE International Conference on Robotics and Automation, vol. 3, pp. 2249–2254.
[8] S. Nakamura, M. Faragalli, N. Mizukami, I. Nakatani, Y. Kunii, and T. Kubota, “Wheeled robot with movable center of mass for traversing over rough terrain,” in 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007, pp. 1228–1233.
[9] J. Morales, J. L. Martinez, A. Mandow, J. Seron, and A. J. Garcia-Cerezo, “Static Tip-Over Stability Analysis for a Robotic Vehicle With a Single-Axle Trailer on Slopes Based on Altered Supporting Polygons,” IEEE/ASME Trans. Mechatronics, vol. 18, no. 2, pp. 697–705, Apr. 2013.
[10] J. Seron, J. L. Martinez, A. Mandow, A. J. Reina, J. Morales, and A. J. Garcia-Cerezo, “Automation of the Arm-Aided Climbing Maneuver for Tracked Mobile Manipulators,” IEEE Trans. Ind. Electron., vol. 61, no. 7, pp. 3638–3647, Jul. 2014.
[11] K. Umemoto and T. Murakami, “A position tracking control of two wheel mobile manipulator using COG trajectory based on zero dynamics,” in IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society, 2012, pp. 2638–2643.
[12] J. Seron et al., “Terrace climbing of the Alacrane mobile robot with cooperation of its onboard arm,” in 2012 12th IEEE International Workshop on Advanced Motion Control (AMC), 2012, pp. 1–6.
[13] X. Ding, Y. Liu, J. Hou, and Q. Ma, “Online Dynamic Tip-Over Avoidance for a Wheeled Mobile Manipulator With an Improved Tip-Over Moment Stability Criterion,” IEEE Access, vol. 7, pp. 67632–67645, 2019.
[14] Q. Huang, S. Sugano, and I. Kato, “Stability control for a mobile manipulator using a potential method,” in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’94), vol. 2, pp. 839–846.
[15] M. H. Korayem, V. Azimirad, A. Nikoobin, and Z. Boroujeni, “Maximum load-carrying capacity of autonomous mobile manipulator in an environment with obstacle considering tip over stability,” Int. J. Adv. Manuf. Technol., vol. 46, no. 5–8, pp. 811–829, Jan. 2010.
[16] M. VUKOBRATOVIĆ and B. BOROVAC, “ZERO-MOMENT POINT — THIRTY FIVE YEARS OF ITS LIFE,” Int. J. Humanoid Robot., vol. 01, no. 01, pp. 157–173, Mar. 2004.
[17] S. A. A. Moosavian and K. Alipour, “On the dynamic tip-over stability of wheeled mobile manipulators,” Int. J. Robot. Autom., vol. 22, no. 4, pp. 322–328, 2007.
[18] M. H. Falsafi, K. Alipour, and B. Tarvirdizadeh, “Tracking-Error Fuzzy-Based Control for Nonholonomic Wheeled Robots,” Arab. J. Sci. Eng., vol. 44, no. 2, pp. 881–892, Feb. 2019.
[19] H. D. Choi, C. J. Lee, and M. T. Lim, “Fuzzy Preview Control for Half-vehicle Electro-hydraulic Suspension System,” Int. J. Control. Autom. Syst., vol. 16, no. 5, pp. 2489–2500, Oct. 2018.
[20] M.-B. Cheng, W.-C. Su, C.-C. Tsai, and T. Nguyen, “Intelligent tracking control of a dual-arm wheeled mobile manipulator with dynamic uncertainties,” Int. J. Robust Nonlinear Control, vol. 23, no. 8, pp. 839–857, May 2013.
[21] Y. Dai, X. Zhu, H. Zhou, Z. Mao, and W. Wu, “Trajectory tracking control for seafloor tracked vehicle by adaptive neural-fuzzy inference system algorithm,” Int. J. Comput. Commun. Control, vol. 13, no. 4, pp. 465–476, 2018.
[22] A. Pandey and D. R. Parhi, “Optimum path planning of mobile robot in unknown static and dynamic environments using Fuzzy-Wind Driven Optimization algorithm,” Def. Technol., vol. 13, no. 1, pp. 47–58, 2017.
[23] Y. Li and Y. Liu, “Real-time tip-over prevention and path following control for redundant nonholonomic mobile modular manipulators via fuzzy and neural-fuzzy approaches,” J. Dyn. Syst. Meas. Control. Trans. ASME, vol. 128, no. 4, pp. 753–764, 2006.
[24] D. J. Purdy, D. Simner, D. Diskett, A. Duncan, P. J. H. Wormell, and C. Stonier, “An experimental and theoretical investigation into the roll-over of tracked vehicles,” Proc. Inst. Mech. Eng. Part D J. Automob. Eng., vol. 230, no. 3, pp. 291–307, Feb. 2016.
[25] J. Li, A. Khajepour, Y. Huang, H. Wang, C. Tang, and Y. Qin, “A new coordinated control strategy for tracked vehicle ride comfort,” Proc. Inst. Mech. Eng. Part K J. Multi-body Dyn., vol. 232, no. 3, pp. 330–341, Sep. 2018.
[26] C. TANG, Y. LI, and X. WU, “Simulation of the Tracked Vehicle Climbing Over Vertical Wall,” DEStech Trans. Eng. Technol. Res., no. amme, 2018.
[27] S. Blažič, I. Škrjanc, and D. Matko, “A robust fuzzy adaptive law for evolving control systems,” Evol. Syst., vol. 5, no. 1, pp. 3–10, Mar. 2014, doi: 10.1007/s12530-013-9084-7.
[28] S. Blažič, I. Škrjanc, and D. Matko, “Globally stable direct fuzzy model reference adaptive control,” Fuzzy Sets Syst., vol. 139, no. 1, pp. 3–33, 2003, doi: 10.1016/S0165-0114(02)00479-7.
[29] T. Haidegger, L. Kovács, S. Preitl, R. E. Precup, B. Benyó, and Z. Benyó, “Controller design solutions for long distance telesurgical applications,” Int. J. Artif. Intell., vol. 6, no. 11 S, pp. 48–71, 2011, Accessed: 07-Aug-2020. [Online]. Available: http://www.aut.upt.ro/~rprecup/Paper_IJAI_2011_Haidegger.pdf.
[30] H. K. Lam, F. H. F. Leung, and P. K. S. Tam, “Stable and robust fuzzy control for uncertain nonlinear systems,” IEEE Trans. Syst. Man, Cybern. Part ASystems Humans., vol. 30, no. 6, pp. 825–840, 2000, doi: 10.1109/3468.895910.
[31] A. Meghdari, D. Naderi, M. A.-2004 J. S. on, and undefined 2004, “Tipover stability estimation for autonomous mobile manipulator using neural network,” academia.edu, Accessed: 07-Aug-2020. [Online]. Available: http://www.academia.edu/download/43428012/TIPOVER_STABILITY_ESTIMATION_FOR_AUTONOM20160306-3457-4dppff.pdf.
[32] A. Ghaffari, A. Meghdari, D. Naderi, and S. Eslami, “Enhancement of the tipover stability of mobile manipulators with non-holonomic constraints using an adaptive neuro-fuzzy-based controller,” Proc. Inst. Mech. Eng. Part I J. Syst. Control Eng., vol. 223, no. 2, pp. 201–213, 2009, doi: 10.1243/09596518JSCE633.
[33] S. U. Amin, K. Agarwal, and R. Beg, “Genetic neural network based data mining in prediction of heart disease using risk factors,” 2013 IEEE Conf. Inf. Commun. Technol. ICT 2013, pp. 1227–1231, 2013, doi: 10.1109/CICT.2013.6558288.
[34] J. Y. (Jo Y. Wong, Theory of ground vehicles. Wiley, 2008.
[35] B. Mashadi and D. Crolla, Vehicle Powertrain Systems. Wiley, 2011.
[36] M. F. Beatty, Principles of engineering mechanics. Volume 2, Dynamics : the analysis of motion. Springer, 2006.
[37] “RecurDyn dynamische und kinematische Mehrkörpersimulation & Mehrkörpersimulationssoftware / multibody dynamics simulation and cae software Why choose RecurDyn as MultiBody Dynamics Software.” [Online]. Available: https://www.functionbay.org/multibody-dynamics-software/why-choose-recurdyn-as-multibody-dynamics-software.html. [Accessed: 23-Sep-2019].
[38] Y. Dai, X. Zhu, L. S. Chen, H. Liu, T. Zhang, and S. J. Liu, “A new multi-body dynamic model for seafloor miner and its trafficability evaluation,” Int. J. Simul. Model., vol. 14, no. 4, pp. 732–743, 2015.
[39] S. Panchal, M. Haji Akhoundzadehr, K. Raahemifar, M. Fowler, and R. Fraser, “Heat and mass transfer modeling and investigation of multiple LiFePO4/graphite batteries in a pack at low C-rates with water-cooling,” Int. J. Heat Mass Transf., vol. 135, pp. 368–377, 2019, doi: 10.1016/j.ijheatmasstransfer.2019.01.076.
[40] A. Safaei, “Adaptive relative velocity estimation algorithm for autonomous mobile robots using the measurements on acceleration and relative distance,” Int. J. Adapt. Control Signal Process., vol. 34, no. 3, pp. 372–388, Mar. 2020, doi: 10.1002/acs.3085.
How to Cite
Satvati, M., Masih-Tehrani, M., Amirkhani, A., & Karimi, M. P. (2020). Fuzzy Arm Controller for Critical Slope Crossing and Quasi-Rotational Strategy for Intense Bump Crossing. Majlesi Journal of Mechatronic Systems, 9(4). Retrieved from http://journals.iaumajlesi.ac.ir/ms/index/index.php/ms/article/view/459