An ideal physical human–robot interaction (pHRI) should offer the users robotic systems that are easy to handle, intuitive to use, ergonomic and adaptive to human habits and preferences. But the variance in the user behavior is often high and rather unpredictable, which hinders the development of such systems. This article introduces a Personalized Adaptive Stiffness controller for pHRI that is calibrated for the user’s force profile and validates its performance in an extensive user study with 49 participants on two different tasks. The user study compares the new scheme to conventional fixed stiffness or gravitation compensation controllers on the 7DOF KUKA LWR IVb by employing two typical jointmanipulation tasks. The results clearly point out the importance of considering task specific parameters and human specific parameters while designing control modes for pHRI. The analysis shows that for simpler tasks a standard fixed controller may perform sufficiently well and that respective task dependency strongly prevails over individual differences. In the more complex task, quantitative and qualitative results reveal differences between the respective control modes, where the Personalized Adaptive Stiffness controller excels in terms of both performance gain and user preference. Further analysis shows that human and task parameters can be combined and quantified by considering the manipulability of a simplified human arm model. The analysis of user’s interaction force profiles confirms this finding.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    A User Study on Personalized Stiffness Control and Task Specificity in Physical Human–Robot Interaction


    Beteiligte:

    Erscheinungsdatum :

    2017-11-24


    Anmerkungen:

    Frontiers in Robotics and AI, vol. 4, art. 58 -- Front. Robot. AI -- http://www.frontiersin.org/Robotics_and_AI -- http://www.bibliothek.uni-regensburg.de/ezeit/?2781824 -- 2296-9144



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    0 / 004 / 6 / 62 / 629




    A User Study on Personalized Stiffness Control and Task Specificity in Physical Human–Robot Interaction

    Gopinathan, Sugeeth / Ötting, Sonja K. / Steil, Jochen J. | BASE | 2017

    Freier Zugriff

    A user study on personalized stiffness control and task specificity in physical Human-Robot Interaction

    Gopinathan, Sugeeth / Ötting, Sonja Kristine / Steil, Jochen J. | BASE | 2017

    Freier Zugriff

    Fault-Tolerant Physical Human-Robot Interaction via Stiffness Adaptation of Elastic Actuators

    Stuhlenmiller, Florian / Velasco-Guillen, Rodrigo J. / Rinderknecht, Stephan et al. | Springer Verlag | 2020


    Fault-Tolerant Physical Human-Robot Interaction via Stiffness Adaptation of Elastic Actuators

    Stuhlenmiller, Florian / Velasco-Guillen, Rodrigo J. / Rinderknecht, Stephan et al. | TIBKAT | 2020


    Identification of Human Dynamics in User-Led Physical Human Robot Environment Interaction

    Haninger, Kevin / Surdilovic, Dragoljub | BASE | 2018

    Freier Zugriff