TY - GEN
T1 - Inverse optimal control for differentially flat systems with application To locomotion modeling
AU - Aghasadeghi, Navid
AU - Bretl, Timothy
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/9/22
Y1 - 2014/9/22
N2 - Inverse optimal control is The problem of computing a cost function with respect To which observed Trajectories of a given dynamic system are optimal. In This paper, we present a new formulation of This problem for The case where The dynamic system is differentially flat. We show That a solution is easy To obtain in This case, in fact reducing To finite-dimensional linear least-squares minimization. We also show how To make This solution robust To model perturbation, sampled data, and measurement noise, as well as provide a recursive implementation for online learning. Finally, we apply our new formulation of inverse optimal control To model human locomotion during stair ascent. Given sparse observations of human walkers, our model predicts joint angle Trajectories for novel stair heights That compare well To motion capture data (R2 = 0.97, RMSE = 1.95 degrees). These exemplar Trajectories are The basis for an automated method of Tuning controller parameters for lower-limb prosthetic devices That extends To locomotion modes other Than level ground walking.
AB - Inverse optimal control is The problem of computing a cost function with respect To which observed Trajectories of a given dynamic system are optimal. In This paper, we present a new formulation of This problem for The case where The dynamic system is differentially flat. We show That a solution is easy To obtain in This case, in fact reducing To finite-dimensional linear least-squares minimization. We also show how To make This solution robust To model perturbation, sampled data, and measurement noise, as well as provide a recursive implementation for online learning. Finally, we apply our new formulation of inverse optimal control To model human locomotion during stair ascent. Given sparse observations of human walkers, our model predicts joint angle Trajectories for novel stair heights That compare well To motion capture data (R2 = 0.97, RMSE = 1.95 degrees). These exemplar Trajectories are The basis for an automated method of Tuning controller parameters for lower-limb prosthetic devices That extends To locomotion modes other Than level ground walking.
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U2 - 10.1109/ICRA.2014.6907746
DO - 10.1109/ICRA.2014.6907746
M3 - Conference contribution
AN - SCOPUS:84929209003
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 6018
EP - 6025
BT - Proceedings - IEEE International Conference on Robotics and Automation
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Conference on Robotics and Automation, ICRA 2014
Y2 - 31 May 2014 through 7 June 2014
ER -