Skip to main content
Log in

New Adaptive Segmented Wheel for Locomotion Improvement of Field Robots on Soft Terrain

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

In this paper, a new adjustable segmented wheel is proposed whose platform is composed of a complex closed-loop scissor mechanism wrapped over adjustable spokes. The new platform composed of four proposed wheels is specified to avoid halting, to increase traction force and to adjust body orientation while interacting soft or composite terrains. The soil contact model (SCM), extended from Bekker’s theory is implemented to derive the wheel-soil interaction formulations. Furthermore, the Lagrange approach is used to derive the unmanned ground vehicle (UGV) dynamics including interaction forces. The best configurations of adjustable wheel are tabulated according to the terrain properties and the motion types. Finally, the proposed UGV is compared with a typical ordinary UGV to investigate traction forces and halting avoidance. Based on the simulation results and primary tests of the experimental setup, it can be inferred that this new mechanism can effectively adapt itself to different terrain conditions in order to pass the soft concave regions, climb the soft obstacles and move on the composite terrains.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Walter, W.G.: An imitation of life. Sci. Am. 182(5), 42–45 (1950) https://www.jstor.org/stable/24967456. Accesed 12 Feb 2019

    Article  Google Scholar 

  2. Tarasenko, M.V.: Transformation of the soviet space program after the cold war. Sci Glob Secur. 4(3), 339–361 (1964). https://doi.org/10.1080/08929889408426406

    Article  Google Scholar 

  3. Board, S.: An Assessment of Balance in NASA's Science Programs. National Academies Press, Washington (2006)

    Google Scholar 

  4. Pedersen, L., Kortenkamp, D., Wettergreen, D., Nourbakhsh, I.: A survey of space robotics. CA, United States. In: Korsmeyer, D. (ed.) NASA technical report server. 20030054507 (2003) Online. Available: https://ntrs.nasa.gov/search.jsp?R=20030054507. Accesed 12 Feb 2019

  5. Durst, P.J., Monroe, G., Bethel, C.L., Anderson, D.T., Carruth, D.W.: A history and overview of mobility modeling for autonomous unmanned ground vehicles. Autonomous Systems: Sensors, Vehicles, Security, and the Internet of Everything (2018). https://doi.org/10.1117/12.2309570

    Book  Google Scholar 

  6. Zhu, Y., Fei, Y., Xu, H.: Stability analysis of a wheel-track-leg hybrid Mobile robot. J Intell Robot Syst. 91(3–4), 515–528 (2018). https://doi.org/10.1007/s10846-017-0724-1

    Article  Google Scholar 

  7. Granosik, G.: Hypermobile robots–the survey. J Intell Robot Syst. 75(1), 147–169 (2014). https://doi.org/10.1007/s10846-013-9985-5

    Article  Google Scholar 

  8. Ding, X., Zheng, Y., Xu, K.: Wheel-legged hexapod robots: a multifunctional mobile manipulating platform. Chinese Journal of Mechanical Engineering 30(1), 3-6 (2017) Online. Available: http://www.cnki.com.cn/Article/CJFDTotal-YJXB201701002.htm. Accesed 12 Feb 2019

  9. Ebrahimi, S., Mardani, A.: Expanding scissor-based UGV for large obstacles climbing. Mechanics Based Design of Structures and Machines. 47(1), 20–36 (2019). https://doi.org/10.1080/15397734.2018.1487845

    Article  Google Scholar 

  10. Ebrahimi, S., Mardani, a.:obstacle climbing improvement of wheeled Mobile robots with extendable bodies. The 5th joint international conference on multibody system dynamics (IMSD), June 24–28. Lisbon, Portugal (2018). http://imsd2018.tecnico.ulisboa.pt/Web_Abstracts_IMSD2018/pdf/WEB_PAPERS/IMSD2018_Full_Paper_106.pdf. Accesed 12 Feb 2019

  11. Dogru, S., Marques, L.: Power characterization of a skid-steered Mobile field robot with an application to headland turn optimization. Journal of Intelligent & Robotic Systems. 93(3–4), 601–615 (2019). https://doi.org/10.1007/s10846-017-0771-7

    Article  Google Scholar 

  12. Ebrahimi, S., Mardani, A.: Terramechanics-based performance enhancement of the wide robotic wheel on the soft terrains, part I: wheel shape optimization. The 4th IEEE International Conference on Robotics and Mechatronics. https://doi.org/10.1109/ICRoM.2017.8466134

  13. Mardani, A., Ebrahimi, S.: Terramechanics-based performance enhancement of the wide robotic wheel on the soft terrains, Part II: torque control of the optimized wheel. The 4th IEEE International Conference on Robotics and Mechatronics. https://doi.org/10.1109/ICRoM.2017.8466156

  14. Krenn, R., Gibbesch, A.: Soft soil contact modeling technique for multi-body system simulation. In: Zavarise, G., Wriggers, P. (ed.) 58, Trends in Computational Contact Mechanics. Lecture Notes in Applied and Computational Mechanics: Springer, Berlin, Heidelberg. (2011)

    Chapter  Google Scholar 

  15. Harnisch, C., Lach, B., Jakobs, R., Troulis, M.: A new Tyre–soil interaction model for vehicle simulation on deformable ground. Veh. Syst. Dyn. 43(sup1), 384–394 (2005). https://doi.org/10.1080/00423110500139981

    Article  Google Scholar 

  16. Ebrahimi, S., Mardani, A.: A new contact angle detection method for dynamics estimation of a UGV subject to slipping in rough-terrain. J Intell Robot Syst. 1–21 (2018). https://doi.org/10.1007/s10846-018-0932-3

    Article  Google Scholar 

  17. Mardani, A., Ebrahimi, S.: Simultaneous surface scanning and stability analysis of wheeled mobile robots using a new spatial sensitive shield sensor. Robot. Auton. Syst. 98, 1–14 (2017). https://doi.org/10.1016/j.robot.2017.08.007

    Article  Google Scholar 

  18. Liu, Z., Guo, J., Ding, L., Gao, H., Guo, T., Denga, D.: Online estimation of terrain parameters and resistance force based on equivalent sinkage for planetary rovers in longitudinal skid. Mech. Syst. Signal Process. 119, 39–54 (2019). https://doi.org/10.1016/j.ymssp.2018.09.017

    Article  Google Scholar 

  19. He, R., Sandu, C., Khan, A.K., Guthrie, A.G., Els, P.S., Hamersma, H.A.: Review of terramechanics models and their applicability to real-time applications. J. Terrramech. 81, 3–22 (2019). https://doi.org/10.1016/j.jterra.2018.04.003

    Article  Google Scholar 

  20. Bekker, M.G.: Theory of Land Locomotion. University of Michigan Press (1956)

  21. Fassbender, F.R., Fervers, C.W., Harnisch, C.: Approaches to predict the vehicle dynamics on soft soil. Veh. Syst. Dyn. 27(S1), 173–188 (1997). https://doi.org/10.1504/IJVP.2019.097099

    Article  Google Scholar 

  22. Irani, R.A., Bauer, R.J., Warkentin, A.: Dynamic wheel-soil model for lightweight mobile robots with smooth wheels. J Intell Robot Syst. 71(2), 179–193 (2013). https://doi.org/10.1007/s10846-012-9777-3

    Article  Google Scholar 

  23. Hutangkabodee, S., Zweiri, Y.H., Seneviratne, L.D.: Soil parameter identification for wheel-terrain interaction dynamics and traversability prediction. Int. J. Autom. Comput. 3(3), 244–251 (2006). https://doi.org/10.1007/s11633-006-0244-0

    Article  Google Scholar 

  24. Zachmann, G.: Virtual reality in assembly simulation-collision detection, simulation algorithms, and interaction techniques. [dissertation]. Zachmann: Gabriel (2000)

  25. Buse, F.: Using superposition of local soil flow fields to improve soil deformation in the DLR soil contact model-SCM. . The 5th Joint International Conference on Multibody System Dynamics (IMSD); June 24–28, Lisbon (2018). http://imsd2018.tecnico.ulisboa.pt/Web_Abstracts_IMSD2018/pdf/WEB_PAPERS/IMSD2018_Full_Paper_14.pdf. Accesed 2 Dec. 2019

  26. Wong, J.Y.: Terramechanics and off-Road Vehicle Engineering: Terrain Behaviour, off-Road Vehicle Performance and Design. Butterworth-Heinemann (2009)

  27. Ghotbi, B., González, F., Kövecses, J., Angeles, J.: Mobility evaluation of wheeled robots on soft terrain: effect of internal force distribution. Mech. Mach. Theory. 100, 259–282 (2016). https://doi.org/10.1016/j.mechmachtheory.2016.02.005

    Article  Google Scholar 

  28. Ding, L., Yang, H., Gao, H., Li, N., Deng, Z., Guo, J., Li, N.: Terramechanics-based modeling of sinkage and moment for in-situ steering wheels of mobile robots on deformable terrain. Mech. Mach. Theory. 116, 14–33 (2017). https://doi.org/10.1016/j.mechmachtheory.2017.05.011

    Article  Google Scholar 

  29. Zeng, W., Gao, F., Jiang, H., Huang, C., Jianxing, L., Hanfei, L.: Design and analysis of a compliant variable-diameter mechanism used in variable-diameter wheels for lunar rover. Mech. Mach. Theory. 125, 240–258 (2018). https://doi.org/10.1016/j.mechmachtheory.2018.03.003

    Article  Google Scholar 

  30. Chen, S.C., Huang, K.J., Chen, W.H., Shen, S.Y., Li, C.H., Lin, P.C.: Quattroped: a leg-wheel transformable robot. IEEE/ASME Transactions on Mechatronics. 19(2), 730–742 (2014). https://doi.org/10.1109/TMECH.2013.2253615

    Article  Google Scholar 

  31. Chen, W.H., Lin, H.S., Lin, Y.M., Lin, P.C.: TurboQuad: a novel leg–wheel transformable robot with smooth and fast behavioral transitions. IEEE Trans. Robot. 33(5), 1025–1040 (2017). https://doi.org/10.1109/TRO.2017.2696022

    Article  Google Scholar 

  32. Sun, T., Xiang, X., Su, W., Wu, H., Song, Y.: A transformable wheel-legged mobile robot: design, analysis and experiment. Robot. Auton. Syst. 98, 30–41 (2017). https://doi.org/10.1016/j.robot.2017.09.008

    Article  Google Scholar 

  33. Bai, L., Guan, J., Chen, X., Hou, J., Duan, W.: An optional passive/active transformable wheel-legged mobility concept for search and rescue robots. Robot. Auton. Syst. 107, 145–155 (2018). https://doi.org/10.1016/j.robot.2018.06.005

    Article  Google Scholar 

  34. Xie, X., Gao, F., Huang, C., Zeng, W.: Design and development of a new transformable wheel used in amphibious all-terrain vehicles (A-ATV). J. Terrramech. 69, 45–61 (2017). https://doi.org/10.1016/j.jterra.2016.11.001

    Article  Google Scholar 

  35. Kim, I., Jeon, W., Yang, H.: Design of a transformable mobile robot for enhancing mobility. Int. J. Adv. Robot. Syst. 14(1), (2017). https://doi.org/10.1177/1729881416687135

    Article  Google Scholar 

  36. Yang, T., Sun, N., Chen, H., Fang, Y.: Neural network-based adaptive antiswing control of an underactuated ship-mounted crane with roll motions and input dead zones. IEEE Transactions on Neural Networks and Learning Systems. 1-14, (2019). https://doi.org/10.1109/TNNLS.2019.2910580

    Article  Google Scholar 

  37. Sun, N., Yang, T., Fang, Y., Wu, Y., Chen, H.: Transportation control of double-pendulum cranes with a nonlinear quasi-PID scheme: design and experiments. IEEE Trans Syst Man Cybern Syst. 49(7), 1408–1418 (2018). https://doi.org/10.1109/TSMC.2018.2871627

    Article  Google Scholar 

  38. Sun, K., Mou, S., Qiu, J., Wang, T., Gao, H.: Adaptive fuzzy control for non-triangular structural stochastic switched nonlinear systems with full state constraints. IEEE Trans Fuzzy Syst. 1 (2018). https://doi.org/10.1109/TFUZZ.2018.2883374

    Article  Google Scholar 

  39. Tran, T.H., Kwok, N.M., Scheding, S., Ha, Q.P.: Dynamic modelling of wheel-terrain interaction of a UGV. IEEE International conference on automation Science and Engineering CASE, AZ, USA. (2007). https://doi.org/10.1109/COASE.2007.4341715

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Saeed Ebrahimi.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mardani, A., Ebrahimi, S. & Alipour, K. New Adaptive Segmented Wheel for Locomotion Improvement of Field Robots on Soft Terrain. J Intell Robot Syst 97, 695–717 (2020). https://doi.org/10.1007/s10846-019-01059-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-019-01059-1

Keywords

Navigation