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From Biomechanics to Robotics

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Biomechanics of Anthropomorphic Systems

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 124))

Abstract

How does the central nervous system select and coordinate different degrees of freedom to execute a given movement? The difficulty is to choose specific motor commands among an infinite number of possible ones. If some invariants of movement can be identified, there exists however considerable variability showing that motor control favors rather an envelope of possible movements than a strong stereotypy. However, the central nervous system is able to find extremely fast solutions to the problem of muscular and kinematic redundancy by producing stable and precise movements. To date, no computational model has made it possible to develop a movement generation algorithm with a performance comparable to that of humans in terms of speed, accuracy, robustness and adaptability. One of the reasons is certainly that correct criteria for the synthesis of movement as a function of the task have not yet been identified and used for motion generation. In this chapter we propose to study highly dynamic human movements taking into account their variability, making the choice to consider performance biomechanical variables (tasks) for generating motions and involving whole-body articulations.

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References

  1. Anderson, F.C., Pandy, M.G.: A dynamic optimization solution for vertical jumping in three dimensions. Comput. Methods Biomech. Biomed. Eng. 2(3), 201–231 (1999)

    Article  Google Scholar 

  2. Ashby, B.M., Delp, S.L.: Optimal control simulations reveal mechanisms by which arm movement improves standing long jump performance. J. Biomech. 39(9), 1726–1734 (2006)

    Article  Google Scholar 

  3. Ashby, B.M., Heegaard, J.H.: Role of arm motion in the standing long jump. J. Biomech. 35(12), 1631–1637 (2002)

    Article  Google Scholar 

  4. Carpentier, J., Valenza, F., Mansard, N. et al.: Pinocchio: fast forward and inverse dynamics for poly-articulated systems https://stack-of-tasks.github.io/pinocchio (2015)

  5. Chaumette, F., Hutchinson, S.: Visual servo control, Part I: basic approaches. IEEE Robot. Autom. Mag. 13(4), 82–90 (2006)

    Article  Google Scholar 

  6. Cheng, K.B., Wang, C.H., Chen, H.C., Wu, C.D., Chiu, H.T.: The mechanisms that enable arm motion to enhance vertical jump performance-A simulation study. J. Biomech. 41(9), 1847–1854 (2008)

    Article  Google Scholar 

  7. Chèze, L., Fregly, B.J., Dimnet, J.: A solidification procedure to facilitate kinematic analyses based on video system data. J. Biomech. 28(7), 879–884 (1995)

    Article  Google Scholar 

  8. De Leva, P.: Adjustments to Zatsiorsky-Seluyanov’s segment inertia parameters. J. Biomech. 29(9), 1223–1230 (1996)

    Article  Google Scholar 

  9. Delp, S.L., Anderson, F.C., Arnold, A.S., Loan, P., Habib, A., John, C.T., Guendelman, E., Thelen, D.G.: Opensim: open-source software to create and analyze dynamic simulations of movement. IEEE Trans. Biomed. Eng. 54(11), 1940–1950 (2007)

    Article  Google Scholar 

  10. Dumas, R., Chèze, L., Verriest, J.-P.: Corrigendum to adjustments to McConville et al. and Young et al. body segment inertial parameters [J. Biomech. 40 (2007) 543553]. J. Biomech. 40(7):1651–1652 (2007)

    Google Scholar 

  11. Dumas, R.: Influence of the 3D inverse dynamic method on the joint forces and moments during gait. J. Biomech. Eng. 129(5), 786 (2007)

    Article  Google Scholar 

  12. Dumas, R., Chèze, L., Verriest, J.P.: Adjustments to Mcconville et al. and Young et al. body segment inertial parameters. J. Biomech. 40(3), 543–553 (2007)

    Article  Google Scholar 

  13. Duprey, S., Chèze, L., Dumas, R.: Influence of joint constraints on lower limb kinematics estimation from skin markers using global optimization. J. Biomech. 43(14), 2858–2862 (2010)

    Article  Google Scholar 

  14. Durkin, J.L., Dowlingm, J.J., Andrews, D.M.: The measurement of body segment inertial parameters using dual energy X-ray absorptiometry. J. Biomech. 35(12), 1575–1580 (2002)

    Article  Google Scholar 

  15. Ehrig, R.M., Taylor, W.R., Duda, G.N., Heller, M.O.: A survey of formal methods for determining the centre of rotation of ball joints. J. Biomech. 39(15), 2798–809 (2005)

    Article  Google Scholar 

  16. Ehrig, R.M., Taylor, W.R., Duda, G.N., Heller, M.O.: A survey of formal methods for determining functional joint axes. J. Biomech. 40(10), 2150–7 (2007)

    Article  Google Scholar 

  17. Escande, A., Mansard, N., Wieber, P.B.: Fast resolution of hierarchized inverse kinematics with inequality constraints. In: 2010 IEEE International Conference on Robotics and Automation, pp. 3733–3738 (May 2010)

    Google Scholar 

  18. Escande, A., Mansard, N., Wieber, P.-B.: Hierarchical quadratic programming: fast online humanoid-robot motion generation. Int. J. Robot. Res. 33(7), 1006–1028 (2014)

    Article  Google Scholar 

  19. Feldman, A.G.: Functional tuning of the nervous system with control of movement or maintenance of a steady posture. II. Controllable parameters of the muscle. Biophysics 11, 565–578 (1966)

    Google Scholar 

  20. Flash, T.: The coordination of arm movements: mathematical model’. J. Neurosci. 5(7), 1688–1703 (1985)

    Article  MathSciNet  Google Scholar 

  21. Gera, G., Freitas, S., Latash, M., Monahan, K., Schoner, G., Scholz, J.: Motor abundance contributes to resolving multiple kinematic task constraints. Mot. Control 14(1), 83–115 (2010)

    Article  Google Scholar 

  22. Hamner, S.R., Seth, A., Delp, S.L.: Muscle contributions to propulsion and support during running. J. Biomech. 43(14), 2709–2716 (2010)

    Article  Google Scholar 

  23. Hatze, H.: A new method for the simultaneous measurement of the moment of inertia, the damping coefficient and the location of the centre of mass of a body segment in situ. Eur. J. Appl. Physiol. 34, 217–226 (1975)

    Article  Google Scholar 

  24. Havana, E.P.: A mathematical model of the human body (Report AMRL-TR-64-102). Technical report, Aerospace Medical Research Laboratory, Ohio (1964)

    Google Scholar 

  25. Hébert, G.: L’éducation physique, virile et morale par la Méthode Naturelle. Tome I: Exposé doctrinal et principes directeurs de travail. Vuibert (1936)

    Google Scholar 

  26. Hickox, L.J., Ashby, B.M., Alderink, G.J.: Exploration of the validity of the two-dimensional sagittal plane assumption in modeling the standing long jump. J. Biomech. 49(7), 1085–1093 (2016)

    Article  Google Scholar 

  27. Hoff, B., Arbib, M.: A model of the effects of speed, accuracy, and perturbation on visually guided reaching. Exp. Brain Res. 22, 285–306 (1992)

    Google Scholar 

  28. Holzbaur, K.R.S., Murray, W.M., Delp, S.L.: A model of the upper extremity for simulating musculoskeletal surgery and analyzing neuromuscular control. Ann. Biomed. Eng. 33(6), 829–840 (2005)

    Article  Google Scholar 

  29. Kanoun, O., Lamiraux, F., Wieber, P.B., Kanehiro, F., Yoshida, E., Laumond, J.P.: Prioritizing linear equality and inequality systems: application to local motion planning for redundant robots. In: 2009 IEEE International Conference on Robotics and Automation, pp. 2939–2944 (2009)

    Google Scholar 

  30. Khatib, O.: A unified approach for motion and force control of robot manipulators: the operational space formulation. IEEE J. Robot. Autom. 3(1), 43–53 (1987)

    Article  Google Scholar 

  31. Kristianslund, E., Krosshaug, T., Van den Bogert, A.J.: Effect of low pass filtering on joint moments from inverse dynamics: implications for injury prevention. J. Biomech. 45(4), 666–671 (2012)

    Article  Google Scholar 

  32. Kuo, A.D.: A least-squares estimation approach to improving the precision of inverse dynamics computations. J. Biomech. Eng. 120(1), 148–59 (1998)

    Article  Google Scholar 

  33. Latash, M.L., Gorniak, S., Zatsiorsky, V.M.: Hierarchies of synergies in human movements. Kinesiology 40(1), 29–38 (2008)

    Google Scholar 

  34. Lu, T.-W., O’Connor, J.J.: Bone position estimation from skin marker co-ordinates using global optimisation with joint constraints. J. Biomech. 32(2), 129–134 (1999)

    Article  Google Scholar 

  35. Maldonado, G., Bitard, H., Watier, B., Souères, P.: Evidence of dynamic postural control performance in parkour landing. Comput. Methods Biomech. Biomed. Eng. 18(1), 1994–1995 (2015)

    Article  Google Scholar 

  36. Mansard, N., Stasse, O., Evrard, P., Kheddar, A.: A versatile generalized inverted kinematics implementation for collaborative working humanoid robots: the Stack of Tasks. In: ICAR’09: International Conference on Advanced Robotics, pp. 1–6, Munich, Germany (June 2009)

    Google Scholar 

  37. Mccaw, S.T., Gardner, J.K., Stafford, L.N., Torry, M.R.: Filtering ground reaction force data affects the calculation and interpretation of joint kinetics and energetics during drop landings. J. Appl. Biomech. 29(6), 804–809 (2013)

    Article  Google Scholar 

  38. Nakamura, Y.: Advanced Robotics: Redundancy and Optimization. Addison-Wesley Pub. Co, Reading, MA (1991)

    Google Scholar 

  39. Orin, D.E., Goswami, A.: Centroidal momentum matrix of a humanoid robot: structure and properties. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 653–659 (September 2008)

    Google Scholar 

  40. Orin, D.E., Goswami, A., Lee, S.-H.: Centroidal dynamics of a humanoid robot. Auton. Robot. 35(2), 161–176 (2013)

    Article  Google Scholar 

  41. Saab, L., Mansard, N., Keith, F., Fourquet, J.Y. , Soueres, P.: Generation of dynamic motion for anthropomorphic systems under prioritized equality and inequality constraints. In: 2011 IEEE International Conference on Robotics and Automation, pp. 1091–1096 (2011)

    Google Scholar 

  42. Saab, L., Ramos, O.E., Keith, F., Mansard, N., Soures, P., Fourquet, J.Y.: Dynamic whole-body motion generation under rigid contacts and other unilateral constraints. IEEE Trans. Rob. 29(2), 346–362 (2013)

    Article  Google Scholar 

  43. Samson, C., Espiau, B., Le Borgne, M.: Robot Control: The Task Function Approach. Oxford University Press, Oxford (1991)

    Google Scholar 

  44. Scholz, J.P., Schöner, G.: The uncontrolled manifold concept: identifying control variables for a functional task. Exp. Brain Res. 126(3), 289–306 (1999)

    Article  Google Scholar 

  45. Seth, A., Sherman, M., Eastman, P., Delp, S.: Minimal formulation of joint motion for biomechanisms. Nonlinear Dyn. 62(1), 291–303 (2010)

    Article  MathSciNet  Google Scholar 

  46. Siciliano, B., Slotine, J.J.E.: A general framework for managing multiple tasks in highly redundant robotic systems. In: Fifth International Conference on Advanced Robotics, 1991. ’Robots in Unstructured Environments’, 91 ICAR, pp. 1211–1216 vol. 2 (June 1991)

    Google Scholar 

  47. Standing, R.J., Maulder, P.S.: A comparison of the habitual landing strategies from differing drop heights of parkour practitioners (traceurs) and recreationally trained individuals. J. Sports Sci. Med. 14(4), 723–731 (2015)

    Google Scholar 

  48. Stasse, O., Flayols, T., Budhiraja, R., Giraud-Esclasse, K., Carpentier, J., Del Prete, A., Souères, P., Mansard, N., Lamiraux, F., Laumond, J.-P., Marchionni, L., Tome, H., Ferro, F.: TALOS: a new humanoid research platform targeted for industrial applications. working paper or preprint (March 2017)

    Google Scholar 

  49. Venture, G., Ayusawa, K., Nakamura, Y.: Motion capture based identification of the human body inertial parameters. In: 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 4575–4578 (2008)

    Google Scholar 

  50. Wakai, M., Linthorne, N.P.: Optimum take-off angle in the standing long jump. Hum. Mov. Sci. 24(1), 81–96 (2005)

    Article  Google Scholar 

  51. Winter, D.A.: Biomechanics and Motor Control of Human Movement, 4th edn. Wiley, New York (2009)

    Book  Google Scholar 

  52. Wu, G., Siegler, S., Allard, P., Kirtley, C., Leardini, A., Rosenbaum, D., Whittle, M., D’Lima, D.D., Cristofolini, L., Witte, H., Schmid, O., Stokes, I.: ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motionPart I: ankle, hip, and spine. J. Biomech. 35(4), 543–548 (2002)

    Article  Google Scholar 

  53. Wu, G., van der Helm, F.C.T., Veeger, H.E.J., Makhsous, M., Van Roy, P., Anglin, C., Nagels, J., Karduna, A.R., McQuade, K., Wang, X., Werner, F.W., Buchholz, B.: ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion. Part II: shoulder, elbow, wrist and hand. J. Biomech. 38(5), 981–992 (2005)

    Article  Google Scholar 

  54. Zatsiorsky, V.M., Seluyanov, V.N.: The mass and inertia characteristics of the main segment of human body. Biomechanics, pp. 1152–1159 (1983)

    Google Scholar 

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Acknowledgements

Part of this work is supported by the European Research Council for the project Actanthrope (ERC-ADG347 340050) and the Flag-Era European project RoboCom++.

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Correspondence to Galo Maldonado .

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Maldonado, G., Souères, P., Watier, B. (2019). From Biomechanics to Robotics. In: Venture, G., Laumond, JP., Watier, B. (eds) Biomechanics of Anthropomorphic Systems. Springer Tracts in Advanced Robotics, vol 124. Springer, Cham. https://doi.org/10.1007/978-3-319-93870-7_3

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