Anthropomorphic Gait Generation using Differential Dynamic Programming with a Reduced Number of Cost Criteria

Bipedal gait is the natural means of human locomotion. Nonetheless, it is still unclear how the central nervous system coordinates the whole-body segments for gait generation. We address this question based on the wellknown hypothesis that the human motion is the result of an optimization process. We consider a reduced set of criteria taken from the observation of human walking and the study of the related literature, which seem to be optimized during the human gait. Differential Dynamic Programming is applied on these criteria with a 3D whole-body skeletal model involving 42 degrees of freedom to generate walking motions. Nine different skeletal models and gaits reconstructed from motion capture data are used to this end. The simulated walking motions are then analyzed and compared to the human reference to show the quality of the gait generation process. The interest of this optimization approach for human-like motion generation is finally discussed.

[1]  Stephen D Prentice,et al.  Swing phase kinetics and kinematics of knee replacement patients during obstacle avoidance. , 2003, Gait & posture.

[2]  Roy Featherstone,et al.  Rigid Body Dynamics Algorithms , 2007 .

[3]  Kazunori Hase,et al.  Human gait simulation with a neuromusculoskeletal model and evolutionary computation , 2003, Comput. Animat. Virtual Worlds.

[4]  P. Souéres,et al.  Angular momentum regulation strategies for highly dynamic landing in Parkour , 2017, Computer methods in biomechanics and biomedical engineering.

[5]  Scott L. Delp,et al.  Full-Body Musculoskeletal Model for Muscle-Driven Simulation of Human Gait , 2016, IEEE Transactions on Biomedical Engineering.

[6]  Philippe Souères,et al.  Human-like gait generation from a reduced set of tasks using the hierarchical control framework from robotics , 2019, 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[7]  M. van de Panne,et al.  Generalized biped walking control , 2010, ACM Trans. Graph..

[8]  KangKang Yin,et al.  SIMBICON: simple biped locomotion control , 2007, ACM Trans. Graph..

[9]  Katja D. Mombaur,et al.  Synthesis of full-body 3-D human gait using optimal control methods , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[10]  Katja D. Mombaur,et al.  Inverse optimal control based identification of optimality criteria in whole-body human walking on level ground , 2016, 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[11]  Justin Carpentier,et al.  On the centre of mass motion in human walking , 2017, Int. J. Autom. Comput..

[12]  Arkady S. Voloshin,et al.  Modeling of heel strike transients during running , 1994 .

[13]  Ajay Seth,et al.  Muscle contributions to propulsion and support during running. , 2010, Journal of biomechanics.

[14]  Vladlen Koltun,et al.  Optimizing locomotion controllers using biologically-based actuators and objectives , 2012, ACM Trans. Graph..

[15]  Mark L. Latash,et al.  The bliss (not the problem) of motor abundance (not redundancy) , 2012, Experimental Brain Research.

[16]  Vincent Bonnet,et al.  Human Arm Motion Analysis Based on the Inverse Optimization Approach , 2018, 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob).

[17]  Ayman Habib,et al.  OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement , 2007, IEEE Transactions on Biomedical Engineering.

[18]  Olivier Stasse,et al.  The Pinocchio C++ library : A fast and flexible implementation of rigid body dynamics algorithms and their analytical derivatives , 2019, 2019 IEEE/SICE International Symposium on System Integration (SII).

[19]  Antonie J van den Bogert,et al.  Estimation of gait kinematics and kinetics from inertial sensor data using optimal control of musculoskeletal models. , 2019, Journal of biomechanics.

[20]  Nicolas Mansard,et al.  Crocoddyl: An Efficient and Versatile Framework for Multi-Contact Optimal Control , 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).

[21]  Martin de Lasa,et al.  Feature-based locomotion controllers , 2010, ACM Trans. Graph..

[22]  Will Tribbey,et al.  Numerical Recipes: The Art of Scientific Computing (3rd Edition) is written by William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery, and published by Cambridge University Press, © 2007, hardback, ISBN 978-0-521-88068-8, 1235 pp. , 1987, SOEN.

[23]  Yujiang Xiang,et al.  Optimization-based prediction of asymmetric human gait. , 2011, Journal of biomechanics.

[24]  Marko Ackermann,et al.  Optimality principles for model-based prediction of human gait. , 2010, Journal of biomechanics.

[25]  Hartmut Witte,et al.  ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion, I: ankle, hip, and spine , 2002 .

[26]  Emanuel Todorov,et al.  Optimal control methods suitable for biomechanical systems , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[27]  Pierre-Brice Wieber,et al.  Holonomy and Nonholonomy in the Dynamics of Articulated Motion , 2006 .

[28]  Sebastian I. Wolf,et al.  Optimal Control Based Stiffness Identification of an Ankle-Foot Orthosis Using a Predictive Walking Model , 2017, Front. Comput. Neurosci..

[29]  Seungmoon Song,et al.  A neural circuitry that emphasizes spinal feedback generates diverse behaviours of human locomotion , 2015, The Journal of physiology.

[30]  Nicolas Mansard,et al.  Differential Dynamic Programming for Multi-Phase Rigid Contact Dynamics , 2018, 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids).

[31]  Bryan Buchholz,et al.  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. , 2005, Journal of biomechanics.

[32]  J. Baumgarte.  Stabilization of constraints and integrals of motion in dynamical systems , 1972 .

[33]  Scott L. Delp,et al.  Predictive Simulation Generates Human Adaptations during Loaded and Inclined Walking , 2015, PloS one.