In this work the authors present a novel algorithm for estimating the odometry of “C” legged robots with compliant legs and an analysis to estimate the pose of the robot. Robots with “C” legs are an alternative to wheeled and tracked robots for overcoming obstacles that can be found in different scenarios like stairs, debris, etc. Therefore, this kind of robot has become very popular for its locomotion capabilities, but at this point these robots do not have developed algorithms to implement autonomous navigation. With that objective in mind, the authors present a novel algorithm using the encoders of the legs to improve the estimation of the robot localization together with other sensors. Odometry is necessary for using some algorithms like the Extended Kalman Filter, which is used for some autonomous navigation algorithms. Due to the flexible properties of the “C” legs and the localization of the rotational axis, obtaining the displacement at every step is not as trivial as in a wheeled robot; to solve those complexities, the algorithm presented in this work makes a linear approximation of the leg compressed instead of calculating in each iteration the mechanics of the leg using finite element analysis, so the calculus level is reduced. Furthermore, the algorithm was tested in simulations and with a real robot. The results obtained in the tests are promising and together with the algorithm and fusion sensor can be used to endow the robots with autonomous navigation. ; The research leading to these results has received funding from RoboCity2030-DIH-CM, 426 Madrid Robotics Digital Innovation Hub, S2018/NMT-4331, funded by “Programas de Actividades I+D en la Comunidad Madrid” and also by the project TASAR (Team of Advanced Search And Rescue Robots), PID2019-105808RB-I00, funded by the Ministerio de Ciencia e Innovación (Government of Spain). ; Peer reviewed


    Access

    Download


    Export, share and cite



    Title :

    A sensor fusion method for pose estimation of c-legged robots



    Publication date :

    2020-11-25


    Remarks:

    1424-8220



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



    Inertial-Joint Learning-Aided Robust Pose Estimation for Legged Robots

    Kim, Yeeun / Choi, Junwan / Myung, Hyun | Springer Verlag | 2024


    Legged robots and methods for controlling legged robots

    LI RONGZHONG | European Patent Office | 2023

    Free access

    Mitigating sensor noise in legged robots

    BLANKESPOOR KEVIN / DA SILVA MARCO | European Patent Office | 2020

    Free access

    Mitigating Sensor Noise in Legged Robots

    BLANKESPOOR KEVIN / DA SILVA MARCO | European Patent Office | 2021

    Free access

    Mitigating sensor noise in legged robots

    BLANKESPOOR KEVIN / DA SILVA MARCO | European Patent Office | 2021

    Free access