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State estimation for biped robots using multibody dynamics

Robert Wittmann, Arne-Christoph Hildebrandt, Daniel Wahrmann, Daniel J. Rixen, Thomas Buschmann

发表年份
2015
引用次数
23

摘要

This paper introduces a new state estimator for biped robots fusing encoder, inertial and force torque measurements. The estimator is implemented as a Kalman filter that uses the dynamical model of the linear inverted pendulum with the center of mass (CoM) state as output. In order to compensate for disturbances and model errors we extend the model by a state for the external force and an additional input which is calculated from the dynamics error in pattern generation. Several simulation results underline the effectiveness of the proposed filter and show its robustness against disturbances. Experimental results and an application example validate the method under real world conditions.

关键词

Control theory (sociology)Inverted pendulumRobustness (evolution)Kalman filterComputer scienceEstimatorRobotTorqueExtended Kalman filterInertial frame of reference

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