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Behavior-Based Segmentation of Demonstrated Task

Nathan Koenig, Maja J. Matarić

Year
2006
Citations
31

Abstract

Abstract — Robot learning from demonstration presents several challenges. Given a task demonstration, the robot must sense, understand, and learn appropriate task attributes. We propose a method for automatic segmentation of a complex demonstration into an ordered set of simpler behaviors. These behaviors present a significantly less complex domain for learning. Our method is based on empirically derived attributes of tasks and simple mathematical transformations that results in a fast and intuitive mechanism for automatic task segmentation. The method is validated on a simulated Pioneer 2 DX platform across four demonstrations that vary in environmental complexity, task complexity, and task strategy. Index Terms — Teaching, demonstration, behavior segmentation I.

Keywords

Task (project management)Computer scienceRobotSegmentationArtificial intelligenceDomain (mathematical analysis)Task analysisSet (abstract data type)Multi-task learningMachine learning

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