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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Velocity Estimation for Quadrupeds Based on Extended Kalman Filter



    Published in:

    Publication date :

    2014-08-11


    Size :

    8 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    VELOCITY ESTIMATION FROM CYCLE PEDALING BY USING EXTENDED KALMAN FILTER ALGORITHM

    PATEL R P / CHAKRABARTI TULIKA / HATI ANANDA SHANKAR et al. | European Patent Office | 2021

    Free access

    Extended Kalman Filter vs. Error State Kalman Filter for Aircraft Attitude Estimation

    Madyastha, Venkatesh / Ravindra, Vishal / Mallikarjunan, Srinath et al. | AIAA | 2011


    Extended Kalman Filter vs. Error State Kalman Filter for Aircraft Attitude Estimation

    Madyastha, V. / Ravindra, V. / Mallikarjunan, S. et al. | British Library Conference Proceedings | 2011


    LOS Rate Estimation Using Extended Kalman Filter

    Kranthi Kumar, R. / Sandhya, R. / Laxman, R. et al. | Springer Verlag | 2019


    Sideslip angle estimation using extended Kalman filter

    Chen,B.C. / Hsieh,F.C. / Nat.Taipei Univ.of Technol.,TW | Automotive engineering | 2008