Robot Learning with Predictions of Operator Intent

Michael T. Rosenstein, Andrew H. Fagg, and Roderic A. Grupen

The goal of this paper is to sketch a scenario for robot learning with remote operation by a person. We are particularly interested in situations where a user interface provides not only feedback about robot performance but also predictions of operator intent. We describe several benefits and challenges of this learning paradigm.


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