Formalizing Assistive Teleoperation

Anca Dragan and Siddhartha Srinivasa
Robotics: Science and Systems, July, 2012.


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Abstract
In assistive teleoperation, the robot helps the user accomplish the desired task, making teleoperation easier and more seamless. Rather than simply executing the user's input, which is hindered by the inadequacies of the interface, the robot attempts to predict the user's intent, and assists in accomplishing it. In this work, we are interested in the scientific underpinnings of assistance: we formalize assistance under the general framework of policy blending, show how previous work methods instantiate this formalism, and provide a principled analysis of its main components: prediction of user intent and its arbitration with the user input. We define the prediction problem, with foundations in Inverse Reinforcement Learning, discuss simplifying assumptions that make it tractable, and test these on data from users teleoperating a robotic manipulator under various circumstances. We propose that arbitration should be moderated by the confidence in the prediction. Our user study analyzes the effect of the arbitration type, together with the prediction correctness and the task difficulty, on the performance of assistance and the preferences of users.

Keywords
teleoperation, intent prediction, human-robot interaction

Notes
Associated Center(s) / Consortia: Quality of Life Technology Center, National Robotics Engineering Center, and Center for the Foundations of Robotics
Associated Lab(s) / Group(s): Personal Robotics

Text Reference
Anca Dragan and Siddhartha Srinivasa, "Formalizing Assistive Teleoperation," Robotics: Science and Systems, July, 2012.

BibTeX Reference
@inproceedings{Dragan_2012_7077,
   author = "Anca Dragan and Siddhartha Srinivasa",
   title = "Formalizing Assistive Teleoperation",
   booktitle = "Robotics: Science and Systems",
   month = "July",
   year = "2012",
}