Skip to main content

Advertisement

Log in

Multi-physics modelling of a compliant humanoid robot

  • Published:
Multibody System Dynamics Aims and scope Submit manuscript

Abstract

We present a multibody simulator being used for compliant humanoid robot modelling and report our reasoning for choosing the settings of the simulator’s key features. First, we provide a study on how the numerical integration speed and accuracy depend on the coordinate representation of the multibody system. This choice is particularly critical for mechanisms with long serial chains (e.g. legs and arms). Our second contribution is a full electromechanical model of the inner dynamics of the compliant actuators embedded in the COMAN robot, since joints’ compliance is needed for the robot safety and energy efficiency. Third, we discuss the different approaches for modelling contacts and selecting an appropriate contact library. The recommended solution is to couple our simulator with an open-source contact library offering both accurate and fast contact modelling. The simulator performances are assessed by two different tasks involving contacts: a bimanual manipulation task and a squatting tasks. The former shows reliability of the simulator. For the latter, we report a comparison between the robot behaviour as predicted by our simulation environment, and the real one.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Notes

  1. One time-unit equals \(\sqrt{l/g}\) seconds, where \(g\) and \(l\) are in \(\mbox{m}/\mbox{s}^{2}\) and m, respectively.

  2. Analytical result was obtained by Maxima computer algebra system [20], with numerical precision of \(3.5\cdot 10^{-14}\).

References

  1. Tsagarakis, N.G., Morfey, S., Cerda, G.M., Zhibin, L., Caldwell, D.G.: Compliant humanoid coman: optimal joint stiffness tuning for modal frequency control. In: IEEE Robotics and Automation, ICRA, pp. 673–678 (2013)

    Google Scholar 

  2. Tsagarakis, N.G., Morfey, S., Dallali, H., Medrano-Cerda, G.A., Caldwell, D.G.: An asymmetric compliant antagonistic joint design for high performance mobility. In: IEEE Intelligent Robots and Systems, IROS, pp. 5512–5517 (2013)

    Google Scholar 

  3. Docquier, N., Poncelet, A., Fisette, P.: ROBOTRAN: a powerful symbolic generator of multibody models. Mech. Sci. 4(1), 199–219 (2013)

    Article  Google Scholar 

  4. Dallali, H., Mosadeghzad, M., Medrano-Cerda, G., Docquier, N., Kormushev, P., Tsagarakis, N., Li, Zh., Caldwell, D.: Development of a dynamic simulator for a compliant humanoid robot based on a symbolic multibody approach. In: IEEE International Conference on Mechatronics, ICM, pp. 598–603 (2013)

    Google Scholar 

  5. Sherman, M.A., Seth, A., Delp, S.L.: Simbody: multibody dynamics for biomedical research. Proc. IUTAM 2, 241–261 (2011)

    Article  Google Scholar 

  6. Van der Noot, N., Colasanto, L., Barrea, A., Van den Kieboom, J., Ronsse, R., Ijspeert, A.J.: Experimental validation of a bio-inspired controller for dynamic walking with a humanoid robot. In: Intelligent Robots and Systems, IROS, pp. 393–400 (2015). IEEE

    Google Scholar 

  7. Dallali, H., Mosadeghzad, M., Medrano-Cerda, G., Vo-Gia L., Tsagarakis, N., Caldwell, D., Gesino, M.: Designing a high performance humanoid robot based on dynamic simulation. In: 2013 European Modelling Symposium, EMS, pp. 359–364 (2013). IEEE

    Chapter  Google Scholar 

  8. Smith, R.: Open Dynamics Engine (ODE). http://www.ode.org/. Accessed 21 June 2016

  9. Mistry, M., Schaal, S., Yamane, K.: Inertial parameter estimation of floating base humanoid systems using partial force sensing. In: 9th IEEE-RAS International Conference on Humanoid Robots, pp. 492–497 (2009). IEEE

    Google Scholar 

  10. Sentis, L.: Synthesis and Control of Whole-Body Behaviors in Humanoid Systems. PhD Thesis, Stanford University (2007)

  11. Fitzpatrick, P., Metta, G., Natale, L.: Towards long-lived robot genes. Robot. Auton. Syst. 56(1), 29–45 (2008)

    Article  Google Scholar 

  12. Habra, T., Dallali, H., Cardellino, A., Natale, L., Tsagarakis, N., Fisette, P., Ronsse, R.: Robotran-YARP interface: a framework for real-time controller developments based on multibody dynamics simulations. In: Multibody Dynamics: Computational Methods and Applications, pp. 147–164. Springer, Berlin (2016)

    Chapter  Google Scholar 

  13. Ivaldi, S., Peters, J., Padois, V., Nori, F.: Tools for dynamics simulation of robots: a survey based on user feedback. In: Proceedings of 2014 IEEE-RAS International Conference on Humanoid Robots, pp. 842–849 (2014). IEEE

    Chapter  Google Scholar 

  14. Boeing, A., Bräunl, Th.: Evaluation of real-time physics simulation systems. In: Proceedings of the 5th International Conference on Computer Graphics and Interactive Techniques in Australia and Southeast Asia, pp. 281–288. ACM, New York (2007)

    Google Scholar 

  15. Todorov, E., Erez, T., Tassa, Y.: MuJoCo: a physics engine for model-based control. In: IEEE Intelligent Robots and Systems, IROS, pp. 5026–5033 (2012)

    Google Scholar 

  16. Samin, J-C., Fisette, P.: Symbolic Modeling of Multibody Systems. Kluwer Academic Publishers, Dordrecht (2003)

    Book  MATH  Google Scholar 

  17. Bullet Physics library. http://bulletphysics.org/. Accessed 21 June 2016

  18. Van den Bergen, G., Gregorius, D.: Game Physics Pearls. AK Peters, Wellesley (2010)

    Book  Google Scholar 

  19. Manual, O.D.E., Wiki: http://ode-wiki.org/wiki/index.php?title=Manual/. Accessed 21 June 2016

  20. Maxima, a Computer Algebra System. http://maxima.sourceforge.net/. Accessed 21 June 2016

  21. Khalil, W., Vijayalingam, A., Khomutenko, B., Mukhanov, I., Lemoine, Ph., Ecorchard, G.: OpenSYMORO: an open-source software package for symbolic modelling of robots. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics Proceedings, pp. 1206–1211 (2014). IEEE

    Google Scholar 

  22. MapleSim—High Performance Physical Modeling and Simulation—Technical Computing Software. http://www.maplesoft.com/products/maplesim/index1.aspx. Accessed 21 June 2016

  23. Spong, M.W.: Modeling and control of elastic joint robots. J. Dyn. Syst. Meas. Control 109(4), 310–318 (1987)

    Article  MATH  Google Scholar 

  24. Siciliano, B., Khatib, O. (eds.): Springer Handbook of Robotics. Springer, Berlin (2008)

    MATH  Google Scholar 

  25. Blau, P.J.: Friction Science and Technology: From Concepts to Applications. CRC Press, Boca Raton (2009)

    Google Scholar 

  26. Chatterjee, A., Ruina, A.: A new algebraic rigid body collision law based on impulse space considerations. J. Appl. Mech. 65(4), 939–951 (1998)

    Article  Google Scholar 

  27. Brogliato, B., ten Dam, A., Paoli, L., Génot, F., Abadie, M.: Numerical simulation of finite dimensional multibody nonsmooth mechanical systems. Appl. Mech. Rev. 55(2), 107–150 (2002)

    Article  Google Scholar 

  28. Drumwright, E., Shell, D.A.: An evaluation of methods for modeling contact in multibody simulation. In: Robotics and Automation, ICRA, pp. 1695–1701 (2011)

    Google Scholar 

  29. Hippmann, G.: An algorithm for compliant contact between complexly shaped bodies. Multibody Syst. Dyn. 12(4), 345–362 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  30. Pérez-González, A., Fenollosa-Esteve, C., Sancho-Bru, J.L., Sánchez-Marín, F.T., Vergara, M., Rodríguez-Cervantes, P.J.: A modified elastic foundation contact model for application in 3D models of the prosthetic knee. Med. Eng. Phys. 30(3), 387–398 (2008)

    Article  Google Scholar 

  31. Simbody: Multibody Physics API. https://simtk.org/projects/simbody. Accessed 21 June 2016

  32. Negrello, F., Garabini, M., Catalano, M.G., Kryczka, P., Choi, W., Caldwell, D., Bicchi, A., Tsagarakis, N.G.: WALK-MAN humanoid lower body design optimization for enhanced physical performance. In: IEEE International Conference on Robotics and Automation, ICRA, pp. 1817–1824 (2016)

    Google Scholar 

  33. Simulators of the COMAN and WALK-MAN humanoid robots. https://gitlab.robotran.be/walkman/coman_robotran/, https://gitlab.robotran.be/walkman/walkman_robotran/. Accessed 21 June 2016

Download references

Acknowledgements

This work is supported by the European Community”s Seventh Framework Programme (FP7/2007-2013) under Grant 611832 (WALK-MAN), by the foundation “Wallonie-Brussel International” (post-doc scholarship awarded to AZ), and by the Belgian F.R.S.-FNRS (Crédit aux Chercheurs #6809010 awarded to RR, Aspirant #16744574 awarded to NVdN).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alexandra A. Zobova.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zobova, A.A., Habra, T., Van der Noot, N. et al. Multi-physics modelling of a compliant humanoid robot. Multibody Syst Dyn 39, 95–114 (2017). https://doi.org/10.1007/s11044-016-9545-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11044-016-9545-4

Keywords

Navigation