Learning impedance controller parameters for lower-limb prostheses

Impedance control is a common framework for control of lower-limb prosthetic devices. This approach requires choosing many impedance controller parameters. In this paper, we show how to learn these parameters for lower-limb prostheses by observation of unimpaired human walkers. We validate our approach in simulation of a transfemoral amputee, and we demonstrate the performance of the learned parameters in a preliminary experiment with a lower-limb prosthetic device.

[1]  C. A. Desoer,et al.  Nonlinear Systems Analysis , 1978 .

[2]  J. Varah.  A Spline Least Squares Method for Numerical Parameter Estimation in Differential Equations , 1982 .

[3]  Neville Hogan,et al.  Impedance Control: An Approach to Manipulation , 1984, 1984 American Control Conference.

[4]  I W Hunter,et al.  System identification of human joint dynamics. , 1990, Critical reviews in biomedical engineering.

[5]  I.W. Hunter,et al.  Identification of time-varying biological systems from ensemble data (joint dynamics application) , 1992, IEEE Transactions on Biomedical Engineering.

[6]  Baake,et al.  Fitting ordinary differential equations to chaotic data. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[7]  D. Winter,et al.  Biomechanical model of the human foot: kinematics and kinetics during the stance phase of walking. , 1993, Journal of biomechanics.

[8]  K. Schittkowski.  Parameter estimation in systems of nonlinear equations , 1994 .

[9]  H. J. de Jongh,et al.  Prosthetic gait of unilateral transfemoral amputees: a kinematic study. , 1995, Archives of physical medicine and rehabilitation.

[10]  N. A. Borghese,et al.  Kinematic determinants of human locomotion. , 1996, The Journal of physiology.

[11]  Stefan Schaal,et al.  Robot Learning From Demonstration , 1997, ICML.

[12]  S. Sastry.  Nonlinear Systems: Analysis, Stability, and Control , 1999 .

[13]  Franck Plestan,et al.  Asymptotically stable walking for biped robots: analysis via systems with impulse effects , 2001, IEEE Trans. Autom. Control..

[14]  Jun Nakanishi,et al.  Learning Movement Primitives , 2005, ISRR.

[15]  Daniel E. Koditschek,et al.  Hybrid zero dynamics of planar biped walkers , 2003, IEEE Trans. Autom. Control..

[16]  Jun Morimoto,et al.  Learning from demonstration and adaptation of biped locomotion , 2004, Robotics Auton. Syst..

[17]  Pieter Abbeel,et al.  Apprenticeship learning via inverse reinforcement learning , 2004, ICML.

[18]  M. R. Osborne,et al.  Parameter estimation of ordinary differential equations , 2005 .

[19]  J. Grizzle,et al.  A Restricted Poincaré Map for Determining Exponentially Stable Periodic Orbits in Systems with Impulse Effects: Application to Bipedal Robots , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[20]  P. James McLellan,et al.  Parameter estimation in continuous-time dynamic models using principal differential analysis , 2006, Comput. Chem. Eng..

[21]  John Guckenheimer,et al.  The Dynamics of Legged Locomotion: Models, Analyses, and Challenges , 2006, SIAM Rev..

[22]  Jiguo Cao,et al.  Parameter estimation for differential equations: a generalized smoothing approach , 2007 .

[23]  Reinhard Blickhan,et al.  Compliant leg behaviour explains basic dynamics of walking and running , 2006, Proceedings of the Royal Society B: Biological Sciences.

[24]  J. Timmer,et al.  Parameter estimation in ordinary differential equations for biochemical processes using the method of multiple shooting. , 2007, IET systems biology.

[25]  N. Brunel.  Parameter estimation of ODE’s via nonparametric estimators , 2007, 0710.4190.

[26]  Anind K. Dey,et al.  Maximum Entropy Inverse Reinforcement Learning , 2008, AAAI.

[27]  Armando Carlos de Pina Filho,et al.  Simulating the Hip and Knee Behavior of a Biped by Means of Nonlinear Oscillators , 2008 .

[28]  Michael Goldfarb,et al.  Design and Control of a Powered Transfemoral Prosthesis , 2008, Int. J. Robotics Res..

[29]  Brett Browning,et al.  A survey of robot learning from demonstration , 2009, Robotics Auton. Syst..

[30]  Michael Goldfarb,et al.  A Control Approach for Actuated Dynamic Walking in Biped Robots , 2009, IEEE Transactions on Robotics.

[31]  Emanuel Todorov,et al.  Inverse Optimal Control with Linearly-Solvable MDPs , 2010, ICML.

[32]  Michael Goldfarb,et al.  Upslope Walking With a Powered Knee and Ankle Prosthesis: Initial Results With an Amputee Subject , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[33]  Aaron M. Dollar,et al.  On the mechanics of the knee during the stance phase of the gait , 2011, 2011 IEEE International Conference on Rehabilitation Robotics.

[34]  Timothy Bretl,et al.  Maximum entropy inverse reinforcement learning in continuous state spaces with path integrals , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[35]  Jan Peters,et al.  Model learning for robot control: a survey , 2011, Cognitive Processing.

[36]  Koushil Sreenath,et al.  A Compliant Hybrid Zero Dynamics Controller for Stable, Efficient and Fast Bipedal Walking on MABEL , 2011, Int. J. Robotics Res..

[37]  Aaron D. Ames,et al.  Motion primitives for human-inspired bipedal robotic locomotion: walking and stair climbing , 2012, 2012 IEEE International Conference on Robotics and Automation.

[38]  Aaron D. Ames,et al.  Outputs of human walking for bipedal robotic controller design , 2012, 2012 American Control Conference (ACC).

[39]  Aaron D. Ames,et al.  From Formal Methods to Algorithmic Implementation of Human Inspired Control on Bipedal Robots , 2012, WAFR.

[40]  Aaron D. Ames,et al.  First Steps toward Automatically Generating Bipedal Robotic Walking from Human Data , 2012 .

[41]  Michael Goldfarb,et al.  A preliminary investigation of powered prostheses for improved walking biomechanics in bilateral transfemoral amputees , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[42]  Timothy Bretl,et al.  Inverse optimal control for a hybrid dynamical system with impacts , 2012, 2012 IEEE International Conference on Robotics and Automation.

[43]  Jonathon W. Sensinger,et al.  Biomimetic virtual constraint control of a transfemoral powered prosthetic leg , 2013, 2013 American Control Conference.

[44]  Daniel Vélez Día,et al.  Biomechanics and Motor Control of Human Movement , 2013 .