This paper describes a modeling method for predicting a human’s task-level intent through the use of Markov Decision Processes. Intent prediction can be used by a robot to improve decision-making when human and robot operate in a shared physical space. This work presumes human and robot goals are independent such that the robot seeks to avoid interfering with the human rather than directly assisting the human. The proposed human intent prediction system transforms goal sequences the human is expected to complete, a limited past action history, and a correlation of observed behaviors with actions into a prediction of the in-progress or next action the humans is most likely to take. An intra-vehicle activity space robotics application example is presented.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Human Intent Prediction Using Markov Decision Processes


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2015-05-18


    Format / Umfang :

    5 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Human Intent Prediction Using Markov Decision Processes

    McGhan, Catharine / Nasir, Ali / Atkins, Ella | AIAA | 2012


    2012-2445 Human Intent Prediction Using Markov Decision Processes

    McGhan, C. / Nasir, A. / Atkins, E. et al. | British Library Conference Proceedings | 2012


    Planning using hierarchical constrained Markov decision processes

    Feyzabadi, S. | British Library Online Contents | 2017



    Ground Delay Program Planning Using Markov Decision Processes

    Cox, Jonathan / Kochenderfer, Mykel J. | AIAA | 2016