When it comes to physical collaboration between humans and robots, robots currently have a shortcoming: their ability to observe and adapt to human dynamics is limited. This leads to inefficient collaboration and unergonomic interaction. In this work, we combine a dynamic phase state system (PSS) based on a network of stable heteroclinic channels (SHC) with Compliant Movement Primitives (CMP). The combination of PSS and CMP enables intuitive human interaction in tasks where humans and robots physically cooperate. The capabilities of the control system were demonstrated in simulations involving helping a humanoid bipedal robot Talos stand up from a squat position by pulling on its hands.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Phase State System for Generating Interactive Behaviors for Humanoid Robots


    Additional title:

    Mechan. Machine Science


    Contributors:

    Conference:

    International Conference on Robotics in Alpe-Adria Danube Region ; 2022 ; Klagenfurt, Austria June 08, 2022 - June 10, 2022



    Publication date :

    2022-04-23


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





    Outlier-Robust State Estimation for Humanoid Robots*

    Piperakis, S / Kanoulas, D / Tsagarakis, NG et al. | BASE | 2020

    Free access

    Statistical Learning for Humanoid Robots

    Vijayakumar, S. / D Souza, A. / Shibata, T. et al. | British Library Online Contents | 2002


    A Human-like Upper-limb Motion Planner: Generating naturalistic movements for humanoid robots

    Gulletta, Gianpaolo / Costa e Silva, Eliana / Erlhagen, Wolfram et al. | BASE | 2021

    Free access

    Technology enhanced learning using humanoid robots

    Diego Reforgiato | BASE | 2021

    Free access