AAAI Publications, Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence

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Make it So: Continuous, Flexible Natural Language Interaction with an Autonomous Robot
Daniel J. Brooks, Constantine Lignos, Cameron Finucane, Mikhail S. Medvedev, Ian Perera, Vasumathi Raman, Hadas Kress-Gazit, Mitch Marcus, Holly A. Yanco

Last modified: 2012-07-15

Abstract


While highly constrained language can be used for robot control, robots that can operate as fully autonomous subordinate agents communicating via rich language remain an open challenge. Toward this end, we developed an autonomous system that supports natural, continuous interaction with the operator through language before, during, and after mission execution. The operator communicates instructions to the system through natural language and is given feedback on how each instruction was understood as the system constructs a logical representation of its orders. While the plan is executed, the operator is updated on relevant progress via language and images and can change the robot's orders. Unlike many other integrated systems of this type, the language interface is built using robust, general purpose parsing and semantics systems that do not rely on domain-specific grammars. This system demonstrates a new level of continuous natural language interaction and a novel approach to using general-purpose language and planning components instead of hand-building for the domain. Language-enabled autonomous systems of this type represent important progress toward the goal of integrating robots as effective members of human teams.

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