Language and Gesture in Virtual Reality: Is a Gesture Worth1000 Words?

Robots are increasingly incorporating multimodal information and human signals to resolve ambiguity in embodied human-robot interaction. Harnessing signals such as gestures may expedite robot exploration in large, outdoor urban environments for supporting disaster recovery operations, where speech may be unclear due to noise or the challenges of a dynamic and dangerous environment. Despite this potential, capturing human gesture and properly grounding it to crowded, outdoor environments remains a challenge. In this work, we propose a method to model human gesture and ground it to spoken language instructions given to a robot for execution in large spaces. We implement our method in virtual reality to develop a workflow for faster future data collection. We present a series of proposed experiments that compare a language-only baseline to our proposed language supplemented by gesture approach, and discuss how our approach has the potential to reinforce the human’s intent and detect discrepancies in gesture and spoken instructions in these large and crowded environments.

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Publication Details

Journal
Proceedings of the AAAI Symposium Series
Published
2025-11-23
DOI
https://doi.org/10.1609/aaaiss.v7i1.36947
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Language and Gesture in Virtual Reality: Is a Gesture Worth1000 Words?

Cory J. Hayes, Cynthia Matuszek, Padraig Higgins, Stephanie M. Lukin
Proceedings of the AAAI Symposium Series
Hand Gesture Recognition Systems
article

Language and Gesture in Virtual Reality: Is a Gesture Worth1000 Words?

Cory J. Hayes, Cynthia Matuszek, Padraig Higgins, Stephanie M. Lukin
article en

Abstract

Robots are increasingly incorporating multimodal information and human signals to resolve ambiguity in embodied human-robot interaction. Harnessing signals such as gestures may expedite robot exploration in large, outdoor urban environments for supporting disaster recovery operations, where speech may be unclear due to noise or the challenges of a dynamic and dangerous environment. Despite this potential, capturing human gesture and properly grounding it to crowded, outdoor environments remains a challenge. In this work, we propose a method to model human gesture and ground it to spoken language instructions given to a robot for execution in large spaces. We implement our method in virtual reality to develop a workflow for faster future data collection. We present a series of proposed experiments that compare a language-only baseline to our proposed language supplemented by gesture approach, and discuss how our approach has the potential to reinforce the human’s intent and detect discrepancies in gesture and spoken instructions in these large and crowded environments.

Proceedings of the AAAI Symposium SeriesVol. 7(1)
DEVCOM Army Research Laboratory (US), University of Maryland, Baltimore County (US)
National Science Foundation
Openalex Percentile: Top 62%
Hand Gesture Recognition Systems
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