Full Dynamics LQR Control for Bipedal Walking

Biped robots that are expected to locomote in human environments require whole-body controllers that can offer precise tracking and well-defined disturbance rejection behavior. Although walking is a complex dynamical task involving both hybrid dynamics and underactuation, it is unclear the level of complexity needed to generate and execute these tasks. Previously in [4], we experimentally evaluated the use of a linear quadratic regulator (LQR) using a linearization of the full robot dynamics together with the contact constraints for static poses. The advantage of the controller is that it explicitly takes into account the coupling between the different joints to create optimal feedback controllers for whole-body coordination. Additionally, this control policy is computationally light weight and shows a reliable push recovery behavior competitive with more sophisticated balance controllers, rejecting impulses up to 11.7 Ns with peak forces of 650 N. Our preliminary results on balancing were very encouraging and we are now exploring how these results can extend to more dynamic tasks such as walking. The major contribution of this work will be an exploration in the of the amount of complexity needed to create whole-body motions for walking.

[1]  Kazuhito Yokoi,et al.  Biped walking pattern generation by using preview control of zero-moment point , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[2]  Pierre-Brice Wieber,et al.  Online walking gait generation with adaptive foot positioning through Linear Model Predictive control , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Alexander Herzog,et al.  Balancing experiments on a torque-controlled humanoid with hierarchical inverse dynamics , 2013, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Gerd Hirzinger,et al.  Posture and balance control for biped robots based on contact force optimization , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

[5]  Stefan Schaal,et al.  Full dynamics LQR control of a humanoid robot: An experimental study on balancing and squatting , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

[6]  Sergey V. Drakunov,et al.  Capture Point: A Step toward Humanoid Push Recovery , 2006, 2006 6th IEEE-RAS International Conference on Humanoid Robots.