Acta Mechanica Sinica

, Volume 33, Issue 3, pp 516–528 | Cite as

Computational dynamics of soft machines

Review Paper

Abstract

Soft machine refers to a kind of mechanical system made of soft materials to complete sophisticated missions, such as handling a fragile object and crawling along a narrow tunnel corner, under low cost control and actuation. Hence, soft machines have raised great challenges to computational dynamics. In this review article, recent studies of the authors on the dynamic modeling, numerical simulation, and experimental validation of soft machines are summarized in the framework of multibody system dynamics. The dynamic modeling approaches are presented first for the geometric nonlinearities of coupled overall motions and large deformations of a soft component, the physical nonlinearities of a soft component made of hyperelastic or elastoplastic materials, and the frictional contacts/impacts of soft components, respectively. Then the computation approach is outlined for the dynamic simulation of soft machines governed by a set of differential-algebraic equations of very high dimensions, with an emphasis on the efficient computations of the nonlinear elastic force vector of finite elements. The validations of the proposed approaches are given via three case studies, including the locomotion of a soft quadrupedal robot, the spinning deployment of a solar sail of a spacecraft, and the deployment of a mesh reflector of a satellite antenna, as well as the corresponding experimental studies. Finally, some remarks are made for future studies.

Keywords

Computational dynamics Multibody system dynamics Absolute nodal coordinate formulation Contact and impact Soft machine Soft robot Deployable space structure 

References

  1. 1.
    Morin, S.A., Shepherd, R.F., Kwok, S.W., et al.: Camouflage and display for soft machines. Science 337, 828–832 (2012)CrossRefGoogle Scholar
  2. 2.
    Rus, D., Tolley, M.T.: Design, fabrication and control of soft robots. Nature 521, 467–475 (2015)CrossRefGoogle Scholar
  3. 3.
    Wehner, M., Truby, R.L., Fitzgerald, D.J., et al.: An integrated design and fabrication strategy for entirely soft, autonomous robots. Nature 536, 451–455 (2016)CrossRefGoogle Scholar
  4. 4.
    Iida, F., Laschi, C.: Soft robotics: challenges and perspectives. Procedia Comput. Sci. 7, 99–102 (2011)CrossRefGoogle Scholar
  5. 5.
    Li, T.F., Li, G.R., Liang, Y.M., et al.: Review of materials and structures in soft robotics. Chin. J. Theor. Appl. Mech. 48, 756–766 (2016)Google Scholar
  6. 6.
    Ajaj, R.M., Beaverstock, C.S., Friswell, M.I.: Morphing aircraft: the need for a new design philosophy. Aerosp. Sci. Technol. 49, 154–166 (2016)CrossRefGoogle Scholar
  7. 7.
    Tsuda, Y., Mori, O., Funase, R., et al.: Achievement of IKAROS—Japanese deep space solar sail demonstration mission. Acta Astronaut. 82, 183–188 (2013)CrossRefGoogle Scholar
  8. 8.
    Wasfy, T.M., Noor, A.K.: Computational strategies for flexible multibody systems. Appl. Mech. Rev. 56, 553–613 (2003)CrossRefGoogle Scholar
  9. 9.
    Gerstmayr, J., Sugiyama, H., Mikkola, A.: Review on the absolute nodal coordinate formulation for large deformation analysis of multibody systems. J. Comput. Nonlinear Dyn. 8, 031016 (2013)CrossRefGoogle Scholar
  10. 10.
    Liu, C., Tian, Q., Hu, H.Y.: New spatial curved beam and shell elements of gradient deficient absolute nodal coordinate formulation. Nonlinear Dyn. 70, 1903–1918 (2012)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Gerstmayr, J., Shabana, A.A.: Analysis of thin beams and cables using the absolute nodal coordinate formulation. Nonlinear Dyn. 45, 109–130 (2006)CrossRefMATHGoogle Scholar
  12. 12.
    Liu, C., Tian, Q., Yan, D., et al.: Dynamic analysis of membrane systems undergoing overall motions, large deformations and wrinkles via thin shell elements of ANCF. Comput. Methods Appl. Mech. Eng. 258, 81–95 (2013)MathSciNetCrossRefMATHGoogle Scholar
  13. 13.
    Chang, H.J., Liu, C., Tian, Q., et al.: Three new triangular shell elements of ANCF represented by Bézier triangles. Multibody Syst. Dyn. 35, 321–351 (2015)MathSciNetCrossRefMATHGoogle Scholar
  14. 14.
    Luo, K., Liu, C., Tian, Q., et al.: An efficient model reduction method for buckling analyses of thin shells based on IGA. Comput. Methods Appl. Mech. Eng. 309, 243–268 (2016)MathSciNetCrossRefGoogle Scholar
  15. 15.
    García De Jalón, J.: Twenty-five years of natural coordinates. Multibody Syst. Dyn. 18, 15–33 (2007)MathSciNetCrossRefMATHGoogle Scholar
  16. 16.
    Liu, C., Tian, Q., Hu, H.Y.: Dynamics of a large scale rigid-flexible multibody system with composite laminated plates. Multibody Syst. Dyn. 26, 283–305 (2011)CrossRefMATHGoogle Scholar
  17. 17.
    Shabana, A.A.: ANCF reference node for multibody system analysis. Proc. Inst. Mech. Eng. Part K J. Multibody Dyn. 229, 109–112 (2014)Google Scholar
  18. 18.
    Volokh, K.Y.: Mechanics of Soft Materials. Israel Institute of Technology (2010)Google Scholar
  19. 19.
    Zhang, Y.Q., Tian, Q., Chen, L.P., et al.: Simulation of a viscoelastic flexible multibody system using absolute nodal coordinate and fractional derivative methods. Multibody Syst. Dyn. 21, 281–303 (2009)CrossRefMATHGoogle Scholar
  20. 20.
    Luo, K., Liu, C., Tian, Q., et al.: Nonlinear static and dynamic analysis of hyper-elastic thin shells via the absolute nodal coordinate formulation. Nonlinear Dyn. 85, 949–971 (2016)MathSciNetCrossRefMATHGoogle Scholar
  21. 21.
    Wang, Q.T., Tian, Q., Hu, H.Y.: Contact dynamics of elasto-plastic thin beams simulated via absolute nodal coordinate formulation. Acta Mech. Sin. 32, 525–534 (2016)Google Scholar
  22. 22.
    Wang, Q.T., Tian, Q., Hu, H.Y.: Dynamic simulation of frictional multi-zone contacts of thin beams. Nonlinear Dyn. 83, 1919–1937 (2016)CrossRefGoogle Scholar
  23. 23.
    Wang, Q.T., Tian, Q., Hu, H.Y.: Dynamic simulation of frictional contacts of thin beams during large overall motions via absolute nodal coordinate formulation. Nonlinear Dyn. 77, 1411–1425 (2014)MathSciNetCrossRefGoogle Scholar
  24. 24.
    Bernardi, C., Debit, N., Maday, Y.: Coupling finite element and spectral methods: first results. Math. Comput. 54, 21–39 (1990)MathSciNetCrossRefMATHGoogle Scholar
  25. 25.
    Seitz, A., Farah, P., Kremheller, J., et al.: Isogeometric dual mortar methods for computational contact mechanics. Comput. Methods Appl. Mech. Eng. 301, 259–280 (2016)MathSciNetCrossRefGoogle Scholar
  26. 26.
    McDevitt, T.W., Laursen, T.A.: A mortar-finite element formulation for frictional contact problems. Int. J. Numer. Methods Eng. 48, 1525–1547 (2000)MathSciNetCrossRefMATHGoogle Scholar
  27. 27.
    Wriggers, P.: Computational Contact Mechanics. Springer, Berlin (2006)CrossRefMATHGoogle Scholar
  28. 28.
    Kocak, S., Akay, H.U.: Parallel Schur complement method for large-scale systems on distributed memory computers. Appl. Math. Model 25, 873–886 (2001)CrossRefMATHGoogle Scholar
  29. 29.
    Shepherda, R.F., Ilievskia, F., Choia, W., et al.: Multigait soft robot. Proc. Natl. Acad. Sci. 108, 20400–20403 (2011)CrossRefGoogle Scholar
  30. 30.
    Zhao, J., Tian, Q., Hu, H.Y.: Deployment dynamics of a simplified spinning IKAROS solar sail via absolute coordinate based method. Acta Mech. Sin. 29, 132–142 (2013)CrossRefGoogle Scholar
  31. 31.
    Zhou, X.J., Zhou, C.Y., Zhang, X.X., et al.: Ground simulation tests of spinning deployment dynamics of a solar sail. J. Vib. Eng. 28, 175–182 (2015)Google Scholar
  32. 32.
    Li, P., Liu, C., Tian, Q., et al.: Dynamics of a deployable mesh reflector of satellite antenna: parallel computation and deployment simulation. J. Comput. Nonlinear Dyn. 11, 061005 (2016)CrossRefGoogle Scholar
  33. 33.
    Wang, Z., Tian, Q., Hu, H.Y.: Dynamics of rigid-flexible multibody systems with uncertain interval parameters. Nonlinear Dyn. 84, 527–548 (2016)MathSciNetCrossRefMATHGoogle Scholar
  34. 34.
    Wang, Z., Tian, Q., Hu, H.Y.: Nonlinear dynamics and chaotic control of a flexible multibody system with uncertain joint clearance. Nonlinear Dyn. 86, 1571–1597 (2016)CrossRefGoogle Scholar

Copyright information

© The Chinese Society of Theoretical and Applied Mechanics; Institute of Mechanics, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.MOE Key Lab of Dynamics and Control of Flight Vehicles, School of Aerospace EngineeringBeijing Institute of TechnologyBeijingChina

Personalised recommendations