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Modeling of rigid-link and compliant joint manipulator using the discrete body dynamics method

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Abstract

Recently, there has been a growing interest in robots with compliant elements. The commonly used methods for modeling their dynamics are multibody dynamics (MBD), recursive algorithms, impulse-based, and Lagrangian formulation. However, the latter method requires a new derivation for each change made to the system, and modeling compliant elements with it can be challenging. To solve complex systems that include compliant elements, a numerical method is necessary. Whereas some methods provide accurate solutions but have high complexity (e.g., MBD), others are quick but inaccurate (e.g., impulse-based). In this paper, we propose a new method, discrete body dynamics (DBD), which offers quick solutions with high accuracy, especially for systems with compliant elements. The method uses springs and dampers to model joints instead of constraints such as a revolute joint and has a complexity of \(O(n)\). We demonstrate the proposed method using single- and three-link manipulators with compliant joints and compare the results to those of ADAMS (a commercial MBD-based program) and the Lagrangian formulation. Our results show that the DBD method well matches with the Lagrangian formulation and is more accurate than the MBD for both compliant and rigid joints.

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To the best of our knowledge, this paper contains no material previously published by any other person. It has not been published elsewhere, and it has not been simultaneously submitted for publication elsewhere.

References

  1. He, W., Yan, Z., Sun, Y., Ou, Y., Sun, C.: Neural-learning-based control for a constrained robotic manipulator with flexible joints. IEEE Trans. Neural Netw. Learn. Syst. 29, 5993–6003 (2018)

    Article  Google Scholar 

  2. Haldane, D.W., Plecnik, M., Yim, J.K., Fearing, R.S.: A power modulating leg mechanism for monopedal hopping. In: IEEE Int. Conf. Intell. Robot. Syst., 2016-Nov, pp. 4757–4764 (2016)

    Google Scholar 

  3. Jin, M., Lee, J., Tsagarakis, N.G.: Model-free robust adaptive control of humanoid robots with flexible joints. IEEE Trans. Ind. Electron. 64, 1706–1715 (2017)

    Article  Google Scholar 

  4. Liu, C., Tian, Q., Hu, H.: Dynamics and control of a spatial rigid-flexible multibody system with multiple cylindrical clearance joints. Mech. Mach. Theory 52, 106–129 (2012)

    Article  Google Scholar 

  5. Rodrigues da Silva, M., Marques, F., Tavares da Silva, M., Flores, P.: A comparison of spherical joint models in the dynamic analysis of rigid mechanical systems: ideal, dry, hydrodynamic and bushing approaches. Multibody Syst. Dyn. 56, 221–266 (2022). https://doi.org/10.1007/s11044-022-09843-y

    Article  MathSciNet  MATH  Google Scholar 

  6. Meng, D., She, Y., Xu, W., Lu, W., Liang, B.: Dynamic modeling and vibration characteristics analysis of flexible-link and flexible-joint space manipulator. Multibody Syst. Dyn. 43, 321–347 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  7. Lee, S.H., Park, T.W., Seo, J.H., Yoon, J.W., Jun, K.J.: The development of a sliding joint for very flexible multibody dynamics using absolute nodal coordinate formulation. Multibody Syst. Dyn. 20, 223–237 (2008)

    Article  MATH  Google Scholar 

  8. Mohamed, Z., Tokhi, M.O.: Command shaping techniques for vibration control of a flexible robot manipulator. Mechatronics 14, 69–90 (2004)

    Article  Google Scholar 

  9. Li, S., Kruszewski, A., Guerra, T.-M., Nguyen, A.-T.: Equivalent-input-disturbance-based dynamic tracking control for soft robots via reduced-order finite-element models. IEEE/ASME Trans. Mechatron. 27(5), 4078–4089 (2022).

    Article  Google Scholar 

  10. Craig, J.J.: Book review: Introduction to robotics: mechanics and control. Int. J. Electr. Eng. Educ. 41, 388 (2004). https://doi.org/10.7227/ijeee.41.4.11

    Article  Google Scholar 

  11. Angeles, J.: Fundamentals of Robotic Mechanical Systems: Theory, Methods, and Algorithms. Springer, New York (2003)

    Book  MATH  Google Scholar 

  12. Docquier, N., Poncelet, A., Fisette, P.: ROBOTRAN: a powerful symbolic generator of multibody models. Mech. Sci. 4, 199–219 (2013). https://doi.org/10.5194/ms-4-199-2013

    Article  Google Scholar 

  13. Khalil, W., Kleinfinger, J.F.: Minimum operations and minimum parameters of the dynamic models of tree structure robots. IEEE J. Robot. Autom. 3, 517–526 (1987). https://doi.org/10.1109/JRA.1987.1087145

    Article  Google Scholar 

  14. Khalil, W., Creusot, D.: SYMORO+: a system for the symbolic modelling of robots. Robotica 15, 153–161 (1997). https://doi.org/10.1017/S0263574797000180

    Article  Google Scholar 

  15. Luh, J.Y.S., Walker, M.W., Paul, R.P.C.: On-line computational scheme for I. J. Dyn. Syst. Meas. Control 102, 69–76 (1980)

    Article  MathSciNet  Google Scholar 

  16. Khalil, W.: Dynamic modeling of robots using recursive Newton–Euler techniques. In: ICINCO 2010 – Proc. 7th Int. Conf. Informatics Control. Autom. Robot., vol. 1 (2010)

    Google Scholar 

  17. Walker, M.W., Orin, D.E.: Efficient dynamic computer simulation of robotic mechanisms. J. Dyn. Syst. Meas. Control 104, 205–211 (1982). https://doi.org/10.1115/1.3139699

    Article  MATH  Google Scholar 

  18. Anderson, K.S., Critchley, J.H.: Improved “order-N” performance algorithm for the simulation of constrained multi-rigid-body dynamic systems. Multibody Syst. Dyn. 9, 185–212 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  19. Slaats, P.M.A.: Recursive Formulations in Multibody Dynamics. Tech. Univ. Eindhoven (1991)

  20. Greenwood, D.T.: Advanced Dynamics. Cambridge University Press, Cambridge (2003)

    Book  Google Scholar 

  21. Rambely, A.S., Halim, N.A., Ahmad, R.R.: A numerical comparison of Langrange and Kane’s methods of an arm segment. In: International Journal of Modern Physics: Conference Series, pp. 68–75. World Scientific Publishing Company, Malacca, Malaysia (2012)

    Google Scholar 

  22. Purushotham, A., Anjeneyulu, J.: Kane’s Method for Robotic Arm Dynamics: a Novel Approach. In: 2nd National Conference on Recent Developments in Mechanical Engineering [RDME-2013], Pune, India, pp. 42–49 (2013)

    Google Scholar 

  23. Sandino, L.A., Bejar, M., Ollero, A.: Tutorial for the application of Kane’s method to model a small-size helicopter tutorial for the application of Kane’s method to model a small-size helicopter. In: Proc. of the 1st Workshop on Research, Development and Education on Unmanned Aerial Systems, Seville, Spain, pp. 162–173 (2011)

    Google Scholar 

  24. Wang, J.T., Huston, R.L.: Kane’s equations with undetermined multipliers — application to constrained multibody systems. J. Appl. Mech. 54, 424–429 (1987)

    Article  MATH  Google Scholar 

  25. Wang, J.T., Huston, R.L.: Computational methods in constrained multibody dynamics: matrix formalisms. Comput. Struct. 29, 331–338 (1988). https://doi.org/10.1016/0045-7949(88)90267-2

    Article  MATH  Google Scholar 

  26. Stoneking, E.T.: Implementation of Kane’s method for a spacecraft composed of multiple rigid bodies central moments of inertia. In: AIAA Guidance, Navigation, and Control (GNC) Conference, vol. 4649, pp. 1–13 (2013)

    Google Scholar 

  27. Vlase, S., Negrean, I., Marin, M., Năstac, S.: Kane’s method-based simulation and modeling robots with elastic elements, using finite element method. Mathematics 8, 1–21 (2020). https://doi.org/10.3390/MATH8050805

    Article  Google Scholar 

  28. Mirtich, B.V.: Impulse-Based Dynamic Simulation of Rigid Body Systems (1996)

    Google Scholar 

  29. Ebrahimi, S., Eberhard, P.: Aspects of contact problems in computational multibody dynamics. In: García Orden, J.C., Goicolea, J.M., Cuadrado, J. (eds.) Multibody Dynamics, pp. 23–47. Springer Netherlands, Dordrecht (2007)

    Chapter  MATH  Google Scholar 

  30. Schmucker, U., Rusin, V., Konyev, M.: Contact processing in the simulation of the multi-body systems. In: 6th EUROSIM Congress on Modelling and Simulation, Ljubljana, Slovenia (2007)

    Google Scholar 

  31. Franco, Y., Shani, M., Gat, G., Shmulevich, I.: Three-dimensional dynamic model for off-road vehicles using discrete body dynamics. J. Terramech. 91, 297–307 (2020)

    Article  Google Scholar 

  32. Gat, G., Franco, Y., Shmulevich, I.: Fast dynamic modeling for off-road track vehicles. J. Terramech. 92, 1–12 (2020)

    Article  Google Scholar 

  33. Ghrist, M.L., Fornberg, B., Reeger, J.A.: Stability ordinates of Adams predictor–corrector methods. BIT Numer. Math. 55, 733–750 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  34. Aschenbrenner, A., Wartzack, S.: A method for the tolerance analysis of bearing seats for cylindrical roller bearings in respect to operating clearance and fatigue life. In: International Conference on Engineering Design, ICED17, Vancouver (2017)

    Google Scholar 

  35. Kertész, M., Palčák, F.: The role of the stiffly stable integrators in nonlinear dynamic simulations. In: APLIMAT 2015 – 14th Conf. Appl. Math. Proc., pp. 446–455 (2015)

    Google Scholar 

  36. Bathe, K.J., Wilson, E.L.: Numerical Methods in Finite Element Analysis. Prentice-Hall, Englewood Cliffs (1976)

    MATH  Google Scholar 

  37. Aguiar-Conraria, L., Soares, M.J.: The continuous wavelet transform: moving beyond uni- and bivariate analysis. J. Econ. Surv. 28, 344–375 (2014)

    Article  Google Scholar 

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YF wrote the main manuscript text and AD supervised the project and overall direction. All authors reviewed the manuscript.

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Correspondence to Amir Degani.

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Franco, Y., Degani, A. Modeling of rigid-link and compliant joint manipulator using the discrete body dynamics method. Multibody Syst Dyn (2023). https://doi.org/10.1007/s11044-023-09897-6

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