In human-human interactions, individuals naturally achieve fluency by anticipating the partner’s actions. This predictive ability is largely lacking in collaborative robots, leading to inefficient human-robot interactions. Fluent meshing in human-robot collaboration requires the robot to make its intentions clear to its human collaborator. We propose a unified generative model of human reaching motions that allows the robot to (a) infer human intent, and then (b) plan its motion to be legible, or intent-expressive. We conducted a study on human reaching motion and constructed an elliptical motion model that is shown to yield a good fit to empirical data. In future studies, we plan to confirm the effectiveness of this model in predicting human intent and conveying robot intent for achieving fluency in human-robot handovers.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Study of Reaching Motions for Collaborative Human-Robot Interaction


    Additional title:

    Springer Proceedings in Advanced Robotics



    Conference:

    International Symposium on Experimental Robotics ; 2018 ; Buenos Aires, Argentina November 05, 2018 - November 08, 2018



    Publication date :

    2020-01-23


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    A Study of Reaching Motions for Collaborative Human-Robot Interaction

    Sheikholeslami, Sara / Lee, Gilwoo / Hart, Justin W. et al. | TIBKAT | 2020


    Programming-by-demonstration of reaching motions for robot grasping

    Skoglund, Alexander / Tegin, Johan / Iliev, Boyko et al. | BASE | 2009

    Free access

    Modeling Variability in Reaching Motions

    Hu, Jennifer / Faraway, Julian J. | SAE Technical Papers | 2001