Systematic derivation of simplified dynamics for humanoid robots

Simplified models such as the inverted pendulum model are often used in humanoid robot control because the full dynamics model of humanoid robots is too complex to design a controller. These models are usually derived from simple mechanical systems that represent the essential properties of the robot dynamics. This method for deriving simplified models is a manual process that heavily relies on the controller developer's intuition. Moreover, mapping the state and input between the original and simplified models requires model-specific code. This paper describes a general method for systematically obtaining simplified models of humanoid robots. We demonstrate an application of derived models to humanoid robot balance control using linear quadratic regulators.

[1]  Hirochika Inoue,et al.  Real-time humanoid motion generation through ZMP manipulation based on inverted pendulum control , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[2]  Benjamin J. Stephens Integral control of humanoid balance , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Christopher G. Atkeson,et al.  Modeling and control of periodic humanoid balance using the Linear Biped Model , 2009, 2009 9th IEEE-RAS International Conference on Humanoid Robots.

[4]  Katsu Yamane,et al.  Simultaneous tracking and balancing of humanoid robots for imitating human motion capture data , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[5]  J. Marsden,et al.  Structure-preserving Model Reduction of Mechanical Systems , 2000 .

[6]  Sung-Hee Lee,et al.  Reaction Mass Pendulum (RMP): An explicit model for centroidal angular momentum of humanoid robots , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[7]  Ambarish Goswami,et al.  Kinematic and dynamic analogies between planar biped robots and the reaction mass pendulum (RMP) model , 2008, Humanoids 2008 - 8th IEEE-RAS International Conference on Humanoid Robots.

[8]  Andrew Lewis,et al.  Model reduction for real-time fluids , 2006, SIGGRAPH '06.

[9]  S. Kajita,et al.  Experimental study of biped dynamic walking , 1996 .

[10]  Russ Tedrake,et al.  LQR-trees: Feedback motion planning on sparse randomized trees , 2009, Robotics: Science and Systems.

[11]  D. Bernstein,et al.  The optimal projection equations for model reduction and the relationships among the methods of Wilson, Skelton, and Moore , 1985 .

[12]  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).

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

[14]  Dinesh K. Pai,et al.  Multiresolution green's function methods for interactive simulation of large-scale elastostatic objects , 2003, TOGS.