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Multimodal Grounding for Embodied AI via Augmented Reality Headsets for Natural Language Driven Task Planning

2023/04/26 by Selma Wanna, Wanna, Selma, Fabian Parra +7 · 1 citation
Engineering · Psychology · #Action Observation and Synchronization #FOS: Computer and information sciences #I.2.4 #I.2.7 #I.2.9 #Robot Manipulation and Learning #Robotics (cs.RO) #Social Robot Interaction and HRI

paper · pdf · doi:10.48550/arxiv.2304.13676

openalex publication_date 2023/04/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Recent advances in generative modeling have spurred a resurgence in the field of Embodied Artificial Intelligence (EAI). EAI systems typically deploy large language models to physical systems capable of interacting with their environment. In our exploration of EAI for industrial domains, we successfully demonstrate the feasibility of co-located, human-robot teaming. Specifically, we construct an experiment where an Augmented Reality (AR) headset mediates information exchange between an EAI agent and human operator for a variety of inspection tasks. To our knowledge the use of an AR headset for multimodal grounding and the application of EAI to industrial tasks are novel contributions within Embodied AI research. In addition, we highlight potential pitfalls in EAI's construction by providing quantitative and qualitative analysis on prompt robustness.

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