Identification of the inertial parameters of a humanoid robot using unactuated dynamics of the base link

The inertial parameters are important to generate motion patterns for humanoid robots. Conventional identification methods can be used to estimate these parameters; however they required the joint torque estimates that can be obtained by modeling of the transmission or by direct measurements. To overcome that issue we have recently developed a new method to estimate the inertial parameters of legged systems. By using the base-link equations only, we obtain a reduced identification model that is free of joint torque estimates. In this paper we propose to apply the method to a human-size humanoid robot. The preliminary experimental results are given and discussed.

[1]  Yoshihiko Nakamura,et al.  Dynamics Identi cation of Humanoid Systems , 2008 .

[2]  Maxime Gautier,et al.  Numerical calculation of the base inertial parameters of robots , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[3]  Gentiane Venture,et al.  Identification of humanoid robots dynamics using floating-base motion dynamics , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  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).

[5]  Atsuo Kawamura,et al.  Robust biped walking with active interaction control between foot and ground , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[6]  Carlos Canudas de Wit,et al.  Friction Models and Friction Compensation , 1998, Eur. J. Control.

[7]  Gentiane Venture,et al.  2P1-F09 Inertial Parameters Identifiability of Humanoid Robot Based on the Baselink Equation of Motion , 2008 .

[8]  Wisama Khalil,et al.  Modeling, Identification and Control of Robots , 2003 .

[9]  Maxime Gautier.  Dynamic identification of robots with power model , 1997, Proceedings of International Conference on Robotics and Automation.

[10]  Yoshihiko Nakamura,et al.  Motion capture based human motion recognition and imitation by direct marker control , 2008, Humanoids 2008 - 8th IEEE-RAS International Conference on Humanoid Robots.

[11]  Masaru Uchiyama,et al.  Moving Base Robotics and Reaction Management Control , 1996 .

[12]  Haruhisa Kawasaki,et al.  Minimum Dynamics Parameters of Tree Structure Robot Models , 1992 .

[13]  Jan Swevers,et al.  Optimal robot excitation and identification , 1997, IEEE Trans. Robotics Autom..

[14]  Maxime Gautier,et al.  New criteria of exciting trajectories for robot identification , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[15]  Gentiane Venture,et al.  Identification of the Dynamic Parameters of a Car: Simulation and Experimental Results , 2003 .

[16]  Jose A. Ventura,et al.  Parallel machine scheduling about an unrestricted due date and additional resource constraints , 2000 .

[17]  Gentiane Venture,et al.  Minimal-set of Inertial Parameters Identification of Legged Robots Using Base-link Dynamics , 2009 .

[18]  Gentiane Venture,et al.  Modeling and Identification of Passenger Car Dynamics Using Robotics Formalism , 2006, IEEE Transactions on Intelligent Transportation Systems.

[19]  Brian Armstrong,et al.  Friction: experimental determination, modeling and compensation , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[20]  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).

[21]  Fouad Bennis,et al.  Symbolic Calculation of the Base Inertial Parameters of Closed-Loop Robots , 1995, Int. J. Robotics Res..