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    (Microsoft PowerPoint - Expos\351.ppt [Mode de compatibilit\351]) (Microsoft PowerPoint - Expos\351.ppt [Mode de compatibilit\351]) Presentation Transcript

    • 1 How to model the bipedy capacity of the walking parameters from the anatomy? Franck Multon 1, Guillaume Nicolas 1, Gilles Berillon 2 1 M2S Lab. « Mouvement Sport Santé », University Rennes 2 2 UPR 2147 CNRS : « Dynamique de l'Évolution Humaine : Individus, Populations, Espèces »
    • Introduction 2 • Bipedalism = « capacity to walk with two supports » • Motion control of walking – Coupled and complex phenomena: physiology, biomechanics, anatomy, neurophysiology, etc. – Problem = Isolating the role of one parameter
    • Differences between species 3 • Joint angles (Whittle, 1991; D’Août et coll., 2004; Hirasaki et coll., 2004) (D’Août 2004) • Ground reaction force (Kimura et coll., 1977, 1990; Alexander, 1991; Li et coll., 1996; Schmitt, 2003) • Mechanical Energies (Cavagna et Kaneko, 1977 ; Wang et coll., 2003) Wang et coll., 2003 Schmitt (2003)
    • Main principles of bipedal 4 locomotion • Energy expenditure minimization (Zarrugh et coll., 1974; Alexander, 1991, 1992, 1997, 2004; Bejan et Marden, 2006) Sockol et coll. (2007) – Kinetic energy (gesticulation) (Williams, 1985 ; Mansour et coll., 1982 Beaupied, 2003) : i =n i =n 1 1 Ec* = EcT + Ec R = ∑ miVGi / R* + ∑ I i ω i2 2 i =1 2 i =1 2 – Internal work(Burdett et coll., 1983 ; Winter, 1990 ; Minetti et coll., 1994 ; Unnithan et coll., 1999) : m n 1  W 3 int ( ) = ∑ ∆ ∑ miVi 2 + I i ω i2 − mi ghi  k =1  i =1 2 
    • Main principles of bipedal 5 locomotion • Minimum Jerk (Flash et Hogan, 1985; Todorov, 2004) t2  d 3 X  • Many other specific knowledge… Jerk = ∫  3 dt   t1  dt  How to use it for determining a range of possible motions knowing anatomical data?
    • Classical approaches 6 • Comparative approach: shape function Tardieu (1983) Focused on a unique part of the skeleton ≠ global system SIMULATION!
    • Simulation based on kinematic 7 models • Direct kinematics – Requires a complete knowledge of the joint angles – Anatomy not directly taken into account unrealistic motions Crompton et coll. (1998) • Inverse kinematics (Boulic et coll. 1992) – Cartesian constraints adaptation – Anatomy in the kinematic chain function
    • Simulation based on kinematic 8 models • Interpolation in a set of motion clips Pronost et coll. (2006) – Interpolation based on anatomical properties – Extrapolation!? – Physically-invalid motions (Safonova et Hodgins, 2006; Pronost et coll., 2007)
    • Dynamic models 9 • Mechanical model – Bones vs. musculoskeletal modeling – Controller (Gorce, 1999; Hodgins, 1995) Gorce (2001) Hodgins (1995) – Based on known trajectories – Unnatural motions – Muscles activations with optimal control (Sellers et coll., 2004) Delp (1990)
    • Overview 10 Hypotheses: Numerical footprints, joint limits, rotation models axes… Original feet’s Computation Feet’s Direct kinematic traj. of the feet’s trajectories model traj. Inverse kinematics Criteria algorithm Simulated motion
    • Numerical model 11 • Digitalization of bones and 3D complete model (Berillon et coll., 2005) – “Lucy” A.L. 288-1 (National Museum of Ethiopia, Addis Abeba) Microscribe 3D-X
    • Inverse kinematics 12 • 11 DOFs for 6 constraints 5 DOFs solution space ( ∆θ = J + ∆X + α I − J + J δ ) Secondary Primary task tasks • Secondary tasks – Main principles of bipedal locomotion (min. energy) – Anatomical constraints (joints limits, natural rest posture hypothesis) • Validation on 10 human subjects – Motion capture with Vicon-MX – Average RMS error < 0.05rad for joint angles – Relative errors < 9%
    • Searching for the correct traj. of the 13 feet • Parametric curve with 7 control points (splines) Decreasing the seach space • Motion warping
    • Minimization functions 14 • Internal work minimization (Alexander, 2003; Burdett et coll., 1983) • Minimum Jerk (Flash, 1985) Optimization loop including IK Application to 10 human subjects, 1 Pan troglodites, 1 Homo sapiens (Museo Antropologia, Universidade de Coimbra, Coimbra, Portugal) , A.L. 288-1
    • Results in humans 15 • Two cases – 8 subjects: almost identical – 2 subjects: incorrect results
    • Results in Pan troglodytes 16 • Original trajectory of the feet = human • Pan troglodytes (Hamann Todd Collection, Cleveland Museum of Natural History, Cleveland, USA) • Inputs: – Step length L=0.4m (Aerts et coll., 2000) – Anthropometric data (Schoonaert et coll., 2007) – Joint limits experimentally evaluated D’Août et coll. (2002) D’Août et coll. (2002) • Different shape than humans • Similar to D’Août et coll. (2002) • WFint moy > 28% / human!
    • Results in Australopithecus 17 afarensis (« Lucy », A.L. 288-1) • Step length = 46cm Laetoli (Leakey et Hay, 1979 ; Leakey et Harris, 1987) • Anthopometric tables = humans & chimpanzee • Original traj. of the feet = human WFint, Laetoli ≅ 30 J/Kg/min ≅ human
    • Changes in step length 18 • Biomechanics: speed and step length naturally selected to decrease energy expenditure (Minetti et coll., 1995) WFint mini for Lpas≅ 35 to 40cm < 15% for Laetoli Laetoli Optimal Step Length?
    • Visualisation 19
    • Conclusion 20 • Promising results even for simplified models – Lower-part of the body – Simplified joints – No feet, just the ankle • Software platform for testing hypotheses – In anthropology modifying the anatomical data – In human movement sciences main principles of human motion control
    • Perspectives 21 • Feet! • Validation on a wider set of species • Taking dynamics into account – Dynamic Stability (Hof, 2008) – Joint torques (Kang et Freeman, 1993) – Muscles (Delp, 1990)
    • 22 Questions?