Skip to main content
SpringerLink
Log in

Modeling and multiobjective optimization of traction performance for autonomous wheeled mobile robot in rough terrain

  • Published:
Journal of Zhejiang University SCIENCE C Aims and scope Submit manuscript

Abstract

Application of terrain-vehicle mechanics for determination and prediction of mobility performance of autonomous wheeled mobile robot (AWMR) in rough terrain is a new research area currently receiving much attention for both terrestrial and planetary missions due to its significant role in design, evaluation, optimization, and motion control of AWMRs. In this paper, decoupled closed form terramechanics considering important wheel-terrain parameters is applied to model and predict traction. Numerical analysis of traction performance in terms of drawbar pull, tractive efficiency, and driving torque is carried out for wheels of different radii, widths, and lug heights, under different wheel slips. Effects of normal forces on wheels are analyzed. Results presented in figures are discussed and used to draw some conclusions. Furthermore, a multiobjective optimization (MOO) method for achieving optimal mobility is presented. The MOO problem is formulated based on five independent variables including wheel radius r, width b, lug height h, wheel slip s, and wheel rotation angle θ with three objectives to maximize drawbar pull and tractive efficiency while minimizing the dynamic traction ratio. Genetic algorithm in MATLAB is used to obtain optimized wheel design and traction control parameters such as drawbar pull, tractive efficiency, and dynamic traction ratio required for good mobility performance. Comparison of MOO results with experimental results shows a good agreement. A method to apply the MOO results for online traction and mobility prediction and control is discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Barrico, C., Antunes, C.H., Pire, D.F., 2009. Robustness analysis in evolutionary multi-objective optimization applied to VAR planning in electrical distribution networks. LNCS, 5482:216–227. [doi:10.1007/978-3-642-01009-5_19]

    Google Scholar 

  • Bekker, M.G., 1956. Theory of Land Locomotion. University of Michigan Press, Ann Arbor, MI.

    Google Scholar 

  • Bekker, M.G., 1960. Off-the-Road Locomotion. University of Michigan Press, Ann Arbor, MI.

    Google Scholar 

  • Bekker, M.G., 1969. Introduction to Terrain-Vehicle Systems. University of Michigan Press, Ann Arbor, MI.

    Google Scholar 

  • Boyd, S., Vandenberghe, L., 2004. Convex Optimization. Cambridge University Press, UK.

    MATH  Google Scholar 

  • Ding, L., Yoshida, K., Nagatani, K., Gao, H., Deng, Z., 2009. Parameter Identification for Planetary Soil Based on a Decoupled Analytical Wheel-Soil Interaction Terra-mechanics Model. Int. Conf. on Intelligent Robots and Systems, p.4122–4127. [doi:10.1109/IROS.2009.5354538]

  • Ding, L., Gao, H., Deng, Z., Nagatani, K., Yoshida, K., 2011a. Experimental study and analysis on driving wheel’s performance for planetary exploration rovers moving in deformable soil. J. Terramech., 48(1):27–45. [doi:10. 1016/j.jterra.2010.08.001]

    Article  Google Scholar 

  • Ding, L., Deng, Z., Gao, H., 2011b. Planetary rover’s wheel-soil interaction mechanics: new challenges and applications for wheeled mobile robots. Intell. Serv. Rob., 4(1):17–38. [doi:10.1007/s11370-010-0080-5]

    Article  Google Scholar 

  • Freitas, G., Gleizer, G., Lizarralde, F., Hsu, L., Dos Reis, N.R.S., 2010. Kinematic reconfigurability control for an environmental mobile robot operating in the Amazon rain forest. J. Field Rob., 27(2):197–216. [doi:10.1002/rob.20334]

    Google Scholar 

  • Goering, C.E., 1989. Engine and Tractor Power. American Society of Agricultural Engineers, USA.

    Google Scholar 

  • Goh, C.K., Tan, K.C., 2009. Evolutionary Multi-objective Optimization in Uncertain Environments. Springer Verlag, Berlin Heidelberg.

    MATH  Google Scholar 

  • Gustafsson, F., 1997. Slip-based tire-road friction estimation. Automatica, 33(6):1087–1099. [doi:10.1016/S0005-1098(97)00003-4]

    Article  MathSciNet  Google Scholar 

  • Iagnemma, K., Dubowsky, S., 2004. Traction control of wheeled robotic vehicles in rough terrain with application to planetary rovers. Int. J. Rob. Res., 23(10–11):1029–1040. [doi:10.1177/0278364904047392]

    Article  Google Scholar 

  • Iagnemma, K., Ward, C.C., 2009. Classification-based wheel slip detection and detector fusion for mobile robots on outdoor terrain. Auton. Rob., 26(1):33–46. [doi:10.1007/ s10514-008-9105-8]

    Article  Google Scholar 

  • Iagnemma, K., Shibly, H., Rzepniewski, A., Dubowsky, S., 2001. Planning and Control Algorithms for Enhanced Rough-Terrain Rover Mobility. Proc. 6th Int. Symp. on Artificial Intelligence, Robotics and Automation in Space, i-SAIRAS.

  • Iagnemma, K., Golda, D., Spenko, M., Dubowsky, S., 2002. Experimental Study of High-Speed Rough-Terrain Mobile Robot Models for Reactive Behaviours. Experimental Robotics VIII, p.654-663. [doi:10.1007/3-540-36268-1_60]

  • Janosi, Z., Hanamoto, B., 1961. Analytical Determination of Drawbar Pull as a Function of Slip for Tracked Vehicles in Deformable Soils. Proc. 1st Int. Conf. on Terrain-Vehicle Systems, p.707–726.

  • Konak, A., Coit, D.W., Smith, A.E., 2006. Multi-objective optimization using genetic algorithms: a tutorial. Rel. Eng. Syst. Safety, 91(9):992–1007. [doi:10.1016/j.ress.2005.11.018]

    Article  Google Scholar 

  • Konjicija, S., Avdagić, Z., 2009. Evolutionary Multi-objective Approach to Control of Mobile Robot in Unknown Environment. 22nd Int. Symp. on Information Communication and Automation Techlogies, p.1–8. [doi:10. 1109/ICAT.2009.5348429

  • Lindgren, D.R., Hague, T., Smith, P.J.P., Marchant, J.A., 2002. Relating torque and slip in an odometric model for an autonomous agricultural vehicle. Auton. Rob., 13(1): 73–86. [doi:10.1023/A:1015682206018]

    Article  MATH  Google Scholar 

  • Liu, W., Winfield, A.F.T., 2010. Modeling and optimization of adaptive foraging in swarm robotic systems. Int. J. Rob. Res., 29(14):1743–1760. [doi:10.1177/0278364910375139]

    Article  Google Scholar 

  • Marler, R.T., Arora, J.S., 2004. Survey of multi-objective optimization methods for engineering. Struct. Multidisc. Optim., 26(6):369–395. [doi:10.1007/s00158-003-0368-6]

    Article  MathSciNet  MATH  Google Scholar 

  • Mastinu, G., Gobbi, M., Miano, C., 2006. Optimal Design of Complex Mechanical Systems: with Application to Vehicle Engineering. Springer-Verlag, Berlin Heidelberg.

    Google Scholar 

  • Miettinen, K., 2008. Introduction to Multiobjective Optimization: Noniterative Approaches. Springer-Verlag, Berlin Heidelberg.

    Google Scholar 

  • Ojeda, L., Borenstein, J., 2004. Methods for the reduction of odometry errors in over-constrained mobile robots. Auton. Rob., 16(3):273–286. [doi:10.1023/B:AURO.0000025791.45313.01]

    Article  Google Scholar 

  • Reina, G., 2006. Methods for Wheel Slip and Sinkage Estimation in Mobile Robots. In: Yussof, H. (Ed.), Robot Localization and Map Building. In Tech, p.561–578.

  • Sato, M., Ishii, K., 2010. Simultaneous optimization of robot structure and control system using evolutionary algorithm. J. Bion. Eng., 7:S185–S190. [doi:10.1016/S1672-6529 (09)60234-1]

    Article  Google Scholar 

  • Schenker, P., Huntsberger, T., Pirjanian, P., Dubowsky, S., Iagnemma, K., Sujan, V., 2003. Rovers for Intelligent, Agile Traverse of Challenging Terrain. 11th Int. Conf. on Advanced Robotics.

  • Schreiber, M., Kutzbach, H.D., 2008. Influence of soil and tire parameters on traction. Res. Agr. Eng., 54(2):43–49.

    Google Scholar 

  • Shibly, H., Iagnemma, K., Dubowsky, S., 2005. An equivalent soil mechanics formulation for rigid wheels in deformable terrain, with application to planetary exploration rovers. J. Terramech., 42(1):1–13. [doi:10.1016/j.jterra.2004.05.002]

    Article  Google Scholar 

  • Sohne, W., 1958. Fundamentals of pressure distribution and soil compaction under tractor tires. Agr. Eng., 39(5):290.

    Google Scholar 

  • Stroud, K.A., 2003. Advanced Engineering Mathematics. Palgrave MacMillan, Houndmills.

    Google Scholar 

  • Vanderplaats, G.N., 1984. Numerical Optimization Techniques for Engineering Design with Applications. McGraw-Hill, New York.

    MATH  Google Scholar 

  • Williams, W., 1995. Genetic Algorithms: a Tutorial. Available from http://www.dbai.tuwien.ac.at/staff/musliu/.../Class9 GATutorial.ppt [Accessed on Aug. 2, 2012].

  • Wong, J.Y., 2001. Theory of Ground Vehicles. John Willey and Sons, New York, p.91–128.

  • Wong, J.Y., 2010. Terramechanics and Off-Road Vehicle Engineering. Elsevier, p.1–10.

  • Wong, J.Y., Reece, A.R., 1967a. Prediction of rigid wheel performance based on the analysis of soil-wheel stresses part I. Performance of driven rigid wheels. J. Terramech., 4(1):81–98. [doi:10.1016/0022-4898(67)90105-X]

    Article  Google Scholar 

  • Wong, J.Y., Reece, A.R., 1967b. Prediction of rigid wheel performance based on the analysis of soil-wheel stresses part II. Performance of towed rigid wheels. J. Terramech., 4(2):7–25. [doi:10.1016/0022-4898(67)90047-X]

    Article  Google Scholar 

  • Xu, H., Zhang, Z.Y., Khalil, A., Kai, X., Gao, X.Z., 2011. Prototypes selection by multi-objective optimal design: application to a reconfigurable robot in sandy terrain. Ind. Rob., 38(6):599–613. [doi:10.1108/01439911111179110]

    Article  Google Scholar 

  • Yoshida, K., 2003. Slip, Traction Control, and Navigation of a Lunar Rover. 7th Int. Symp. on Artificial Intelligence, Robotics and Automation in Space.

  • Yoshida, K., Hamano, H., 2002. Motion dynamics and control of a planetary rover with slip-based traction model. Proc. SPIE, 4715:275–286. [doi:10.1117/12.474459]

    Article  Google Scholar 

  • Young, R.N., Fattah, E.A., Kiadas, N., 1984. Development in Agricultural Engineering. Vehicle Traction Mechanics. Elsevier, Amsterdam, p.45–94.

    Google Scholar 

  • Zoz, F.M., Grisso, R.D., 2003. Traction and Tractor Performance. ASAE Distinguished Lecture Series, Tractor Design, p.1–45.

Download references

Author information

Authors and Affiliations

  1. College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, 150001, China

    Ozoemena Anthony Ani, He Xu, Yi-ping Shen, Shao-gang Liu & Kai Xue

Authors
  1. Ozoemena Anthony Ani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. He Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yi-ping Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shao-gang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kai Xue
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to He Xu.

Additional information

Project supported by the National Natural Science Foundation of China (No. 60775060), the Natural Science Foundation of Heilongjiang Province of China (No. F200801), the Specialized Research Fund for the Doctoral Program of Higher Education (Nos. 200802171053 and 20102304110006), and the Harbin Science and Technology Innovation Talents Special Fund (No. 2012RFXXG059), China

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ani, O.A., Xu, H., Shen, Yp. et al. Modeling and multiobjective optimization of traction performance for autonomous wheeled mobile robot in rough terrain. J. Zhejiang Univ. - Sci. C 14, 11–29 (2013). https://doi.org/10.1631/jzus.C12a0200

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1631/jzus.C12a0200

Key words

CLC number

Search

Navigation