Collaborative effort towards common ground in situated human-robot dialogue

Chai, Joyce; She, Lanbo; Fang, Rui; Ottarson, Spencer; Littley, Cody; Liu, Changsong; Hanson, Kenneth M.

doi:10.1145/2559636.2559677

Cited by 60 publications

(39 citation statements)

References 21 publications

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“…The property names are arbitrary as long as they are consistent. In contrast, previous work in rr (e.g., Chai et al, 2014;Iida et al, 2011) used a hand-coded concept-labelled semantic representation and checked if aspects of the re match that of a particular object. If so, a binary compatibility feature was set.…”

Section: Discussionmentioning

confidence: 99%

A simple generative model of incremental reference resolution for situated dialogue

Kennington

Schlangen

2017

Computer Speech & Language

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Section: Discussionmentioning

confidence: 99%

A simple generative model of incremental reference resolution for situated dialogue

Kennington

Schlangen

2017

Computer Speech & Language

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“…The robot needs to be able to describe its internal representation of the shared environment so that the human understands what it is talking about. This is particularly important for establishing common ground and supporting successful interaction [1,28]. Toward this goal, this paper explores embodied collaborative referring expression generation which incorporates nonverbal modalities in the collaborative process of referential communication.…”

Section: Discussionmentioning

confidence: 99%

Embodied Collaborative Referring Expression Generation in Situated Human-Robot Interaction

Fang

Doering

Chai

2015

Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction

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To facilitate referential communication between humans and robots and mediate their differences in representing the shared environment, we are exploring embodied collaborative models for referring expression generation (REG). Instead of a single minimum description to describe a target object, episodes of expressions are generated based on human feedback during human-robot interaction. We particularly investigate the role of embodiment such as robot gesture behaviors (i.e., pointing to an object) and human's gaze feedback (i.e., looking at a particular object) in the collaborative process. This paper examines different strategies of incorporating embodiment and collaboration in REG and discusses their possibilities and challenges in enabling human-robot referential communication.

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“…Built upon our previous work on collaborative dialogue for establishing common ground between humans and robots [2], we are investigating the use of dialogue for exception handling. The idea is that, when an exception occurs, the robot should communicate such exception to the human user so that the robot and the user can collaboratively handle these exceptions through dialogue.…”

Section: Discussionmentioning

confidence: 99%

Exception Handling for Natural Language Control of Robots

She

Jia

et al. 2015

Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction Extended Abstracts

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Enabling natural language control of robots is challenging, since human users are often not familiar with the underlying robotic system, and its capabilities and limitations. Many exceptions may occur when natural language commands are translated into lower-level robot actions. This paper gives a brief introduction to three levels of exceptions and discusses how dialogue can be applied to handle these exceptions during human-robot interaction.

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Collaborative effort towards common ground in situated human-robot dialogue

Cited by 60 publications

References 21 publications

A simple generative model of incremental reference resolution for situated dialogue

A simple generative model of incremental reference resolution for situated dialogue

Embodied Collaborative Referring Expression Generation in Situated Human-Robot Interaction

Exception Handling for Natural Language Control of Robots

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