Velocity Estimation for Quadrupeds Based on Extended Kalman Filter

Man Tian Li; Cong Wei Wang; Peng Fei Wang

doi:10.4028/www.scientific.net/KEM.621.525

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HomeKey Engineering MaterialsKey Engineering Materials Vol. 621Velocity Estimation for Quadrupeds Based on...

Velocity Estimation for Quadrupeds Based on Extended Kalman Filter

Abstract:

Measuring robots’ real-time velocity correctly is important for locomotion control. Inertial Measurement Unit (IMU) is widely used for velocity measurement. Limited by the bias and random error, IMU alone often can’t meet the requirement. This paper makes use of Extended Kalman Filter (EKF) to fuse kinematics and IMU, and inhibits the drift successfully. We calibrate the bias and recognize the random errors of IMU. Then the forward kinematics of legs is established and the EKF algorithm for velocity estimation is designed based on IMU and kinematics. Finally, the presented algorithm is validated in simulation and on a quadruped robot based on hydraulic driver in trotting gait.

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Periodical:

Key Engineering Materials (Volume 621)

Pages:

525-532

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.621.525

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Online since:

August 2014

Authors:

Man Tian Li, Cong Wei Wang, Peng Fei Wang*

Keywords:

EKF, IMU, Kinematics, Quadruped, Velocity Estimation

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* - Corresponding Author

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