Interactive Hierarchical Task Learning from a Single Demonstration

We have developed learning and interaction algorithms to support a human teaching hierarchical task models to a robot using a single demonstration in the context of a mixed-initiative interaction with bi-directional communication. In particular, we have identified and implemented two important heuri...

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Bibliographic Details
Published in:	Hri '15: ACM/IEEE International Conference on Human-Robot Interaction USB Stick pp. 205 - 212
Main Authors:	Mohseni-Kabir, Anahita, Rich, Charles, Chernova, Sonia, Sidner, Candace L., Miller, Daniel
Format:	Conference Proceeding
Language:	English
Published:	ACM 01.03.2015
Subjects:	Automobiles Bidirectional control Collaboration Graphical user interfaces Hierarchical Task Networks Learning From Demonstration Robots Task analysis Tires
Online Access:	Get full text
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Summary:	We have developed learning and interaction algorithms to support a human teaching hierarchical task models to a robot using a single demonstration in the context of a mixed-initiative interaction with bi-directional communication. In particular, we have identified and implemented two important heuristics for suggesting task groupings based on the physical structure of the manipulated artifact and on the data flow between tasks. We have evaluated our algorithms with users in a simulated environment and shown both that the overall approach is usable and that the grouping suggestions significantly improve the learning and interaction.
DOI:	10.1145/2696454.2696474