Identification of humanoid robots dynamics using floating-base motion dynamics

When simulating and controlling robot dynamics it is necessary to know the inertial parameters and the joint dynamics accurately. As these parameters are usually not provided by manufacturers, identification is then an essential step in robotics. In addition with the up coming wide-spreading of humanoid robots in the society the identification of humanoid dynamics has became mandatory to insure safety. This paper proposes a method to estimate humanoid robots inertial parameters using a minimal set of sensors. Only joint angles and external forces information are required. Simulations have provided exciting trajectories that are reproduced on a small-size humanoid robot. Experimental results are given.

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

[2]  Maxime Gautier,et al.  Dynamic identification and control of a nonholonomic mobile robot , 1995, Proceedings of International Conference on Control Applications.

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

[4]  Katsu Yamane,et al.  Natural Motion Animation through Constraining and Deconstraining at Will , 2003, IEEE Trans. Vis. Comput. Graph..

[5]  Yoshihiko Nakamura,et al.  Architectural design of miniature anthropomorphic robots towards high-mobility , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  M. Gautier,et al.  Exciting Trajectories for the Identification of Base Inertial Parameters of Robots , 1991, [1991] Proceedings of the 30th IEEE Conference on Decision and Control.

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

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

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

[10]  Yoshihiko Nakamura,et al.  Balanced micro/macro contact model for forward dynamics of rigid multibody , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

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

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

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

[14]  Steven Dubowsky,et al.  An optimal information method for mobile manipulator dynamic parameter identification , 2003 .

[15]  Guangjun Liu,et al.  A base force/torque sensor approach to robot manipulator inertial parameter estimation , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[16]  Philippe Lemoine,et al.  Identification of the payload inertial parameters of industrial manipulators , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[17]  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).

[18]  Gene H. Golub,et al.  A Resampling Method for Computer Vision , 2000 .