Izvorni znanstveni članak
https://doi.org/10.7305/automatika.2015.04.593
Open Solution for Humanoid Attitude Estimation through Sensory Integration and Extended Kalman Filtering
Paolo Pierro
; System Engineering and Automation Department, Higher Polytechnic School, University Carlos III of Madrid, Avenida de la Universidad 30, 28911 Leganés, Madrid, Spain
Concepción Alicia Monje
; System Engineering and Automation Department, Higher Polytechnic School, University Carlos III of Madrid, Avenida de la Universidad 30, 28911 Leganés, Madrid, Spain
Nicolas Mansard
; Laboratory of Analysis and Systems Architecture, LASS-CNRS, 7 Avenue du Colonel Roche, 31077 Toulouse Cedex 4, France
Philippe Soueres
; Laboratory of Analysis and Systems Architecture, LASS-CNRS, 7 Avenue du Colonel Roche, 31077 Toulouse Cedex 4, France
Carlos Balaguer
; System Engineering and Automation Department, Higher Polytechnic School, University Carlos III of Madrid, Avenida de la Universidad 30, 28911 Leganés, Madrid, Spain
Sažetak
In this paper an Extended Kalman Filter (EKF) is used in order to estimate the real state of a humanoid robot (HRP-2 robot in our case study) using the combination of the information coming from the encoders (kinematics) and from the Inertial Measurement Unit (IMU). The integration of the kinematic information into the Kalman filtering process allows a good estimation of the attitude and reduces the complexity of the problem to the use of simple kinematic transformations, even considering the existence of accelerations and mechanical flexibilities in the robot. The EKF estimator presented here is an open solution directly applicable to any humanoid robot, which is the main contribution of our approach. Experimental results are given showing the good performance of the method.
Ključne riječi
Humanoid robot; Attitude estimation; Kalman filtering; Sensor integration; Kinematics simplicity
Hrčak ID:
139720
URI
Datum izdavanja:
8.6.2015.
Posjeta: 1.516 *