Inferring User Intent for Learning by Observation (2004)
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@TECHREPORT{Dixon04inferringuser,
author = {Kevin R. Dixon and Pradeep K. Khosla and Bruce H. Krogh and Maja J. Mataric and Christiaan J. J. Paredis and Sebastian B. Thrun},
title = {Inferring User Intent for Learning by Observation},
institution = {},
year = {2004}
}
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Abstract
Despite the numerous advances in human-robot interaction, most development systems still require that users have substantial knowledge of procedural-programming techniques as well as the specific robot system at hand. For the vast majority of the population, this effectively precludes the use of robots in most cases. If robots are to make headway into everyday situations, then users must be able to program robots in a more natural and intuitive manner. This dissertation explores a method of programming robots to automate motor tasks by inferring the intent of users based on demonstrations of a task. In order to understand such a system, we decompose it into simpler components: modeling user subgoal selection and the response of users to different conditions.
