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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
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)
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)
Ashby, B.M., Heegaard, J.H.: Role of arm motion in the standing long jump. J. Biomech. 35(12), 1631–1637 (2002)
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)
Chaumette, F., Hutchinson, S.: Visual servo control, Part I: basic approaches. IEEE Robot. Autom. Mag. 13(4), 82–90 (2006)
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)
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)
De Leva, P.: Adjustments to Zatsiorsky-Seluyanov’s segment inertia parameters. J. Biomech. 29(9), 1223–1230 (1996)
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)
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)
Dumas, R.: Influence of the 3D inverse dynamic method on the joint forces and moments during gait. J. Biomech. Eng. 129(5), 786 (2007)
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)
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)
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)
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)
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)
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)
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)
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)
Flash, T.: The coordination of arm movements: mathematical model’. J. Neurosci. 5(7), 1688–1703 (1985)
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)
Hamner, S.R., Seth, A., Delp, S.L.: Muscle contributions to propulsion and support during running. J. Biomech. 43(14), 2709–2716 (2010)
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)
Havana, E.P.: A mathematical model of the human body (Report AMRL-TR-64-102). Technical report, Aerospace Medical Research Laboratory, Ohio (1964)
Hébert, G.: L’éducation physique, virile et morale par la Méthode Naturelle. Tome I: Exposé doctrinal et principes directeurs de travail. Vuibert (1936)
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)
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)
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)
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)
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)
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)
Kuo, A.D.: A least-squares estimation approach to improving the precision of inverse dynamics computations. J. Biomech. Eng. 120(1), 148–59 (1998)
Latash, M.L., Gorniak, S., Zatsiorsky, V.M.: Hierarchies of synergies in human movements. Kinesiology 40(1), 29–38 (2008)
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)
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)
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)
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)
Nakamura, Y.: Advanced Robotics: Redundancy and Optimization. Addison-Wesley Pub. Co, Reading, MA (1991)
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)
Orin, D.E., Goswami, A., Lee, S.-H.: Centroidal dynamics of a humanoid robot. Auton. Robot. 35(2), 161–176 (2013)
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)
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)
Samson, C., Espiau, B., Le Borgne, M.: Robot Control: The Task Function Approach. Oxford University Press, Oxford (1991)
Scholz, J.P., Schöner, G.: The uncontrolled manifold concept: identifying control variables for a functional task. Exp. Brain Res. 126(3), 289–306 (1999)
Seth, A., Sherman, M., Eastman, P., Delp, S.: Minimal formulation of joint motion for biomechanisms. Nonlinear Dyn. 62(1), 291–303 (2010)
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)
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)
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)
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)
Wakai, M., Linthorne, N.P.: Optimum take-off angle in the standing long jump. Hum. Mov. Sci. 24(1), 81–96 (2005)
Winter, D.A.: Biomechanics and Motor Control of Human Movement, 4th edn. Wiley, New York (2009)
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)
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)
Zatsiorsky, V.M., Seluyanov, V.N.: The mass and inertia characteristics of the main segment of human body. Biomechanics, pp. 1152–1159 (1983)
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++.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this chapter
Cite this chapter
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-93870-7_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-93869-1
Online ISBN: 978-3-319-93870-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)