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.


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    Title :

    Human Intent Prediction Using Markov Decision Processes


    Contributors:

    Published in:

    Publication date :

    2015-05-18


    Size :

    5 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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