@inproceedings{55d17916cf71413a9cf27dce5a36b66d,
title = "State estimation for biped robots using multibody dynamics",
abstract = "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.",
keywords = "Dynamics, Foot, Force measurement, Mathematical model, Planning, Robot sensing systems",
author = "Robert Wittmann and Hildebrandt, {Arne Christoph} and Daniel Wahrmann and Daniel Rixen and Thomas Buschmann",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 ; Conference date: 28-09-2015 Through 02-10-2015",
year = "2015",
month = dec,
day = "11",
doi = "10.1109/IROS.2015.7353667",
language = "English",
series = "IEEE International Conference on Intelligent Robots and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2166--2172",
booktitle = "IROS Hamburg 2015 - Conference Digest",
}