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Today, on Global Accessibility Awareness Day, we're rolling out new ...
21 hours ago ... Simply say: "Hey Meta, Be My Eyes with [name or company]" Meta AI will recognize the request, search your private groups or the public Service Directory, and ...
FAM-HRI: Foundation-Model Assisted multimodal Human-Robot ...
Yuzhi Lai1, Shenghai Yuan2, Peizheng Li1,3, Boya Zhang1, Benjamin Kiefer1, Tianchen Deng2,4 and Andreas Zell1 Corresponding Author: Andreas Zell. This work was supported in part by Meta, and we acknowledge their contribution of Meta Glasses for this research.1University of Tuebingen, Geschwister-Scholl-Platz, 72074 Germany, {name.surname}@uni-tuebingen.de.2Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, shyuan@ntu.edu.sg.3peizheng.li@mercedes-benz.com.4N2308684A@e.ntu.edu.sg. Abstract Effective Human-Robot Interaction (HRI) is crucial for enhancing accessibility and usability in real-world robotics applications. However, existing solutions often rely on gesture-only or language-only commands, making interaction inefficient and ambiguous, particularly for users with physical impairments. In this paper, we introduce FAM-HRI, an efficient multimodal framework for HRI that integrates language and gaze inputs via foundation models. By leveraging lightweight Meta ARIA glasses, our system captures real-time multimodal signals and utilizes large language models (LLMs) to fuse user intention with scene context, enabling intuitive and precise robot manipulation. Our method accurately determines the gaze fixation time interval, reducing noise caused by the gaze dynamic nature. Experimental evaluations demonstrate that FAM-HRI achieves a high success rate in task execution while maintaining a low interaction time, providing a practical solution for individuals with limited physical mobility or motor impairments. To support the community, we have released our system design, algorithms, and solutions at https://github.com/laiyuzhi/FAM-HRI. Note to Practitioners In the field of assistive and service robotics, enabling users with physical disabilities to communicate intentions naturally remains a significant challenge. Existing uni-modal approaches, such as voice-only or gaze-only interaction, often struggle with ambiguity and environmental interference, limiting their reliability in real-world scenarios. Current multimodal systems typically process gaze and speech separately, making it difficult to align visual attention with oral commands accurately. Additionally, many systems rely on bulky hardware or require users to maintain prolonged focus, reducing practicality and comfort. To address these issues, this paper proposes a foundation-model-assisted multimodal human-robot interaction (FAM-HRI) framework that combines lightweight AR glasses with...
Yelp adds AI-powered alt text and new ways to search for accessible ...
... access to assistive technologies on their own devices). SEE ALSO: Apple adds new accessibility features across the senses, including eye tracking. The updated ...
What thoughtful gifts enhance daily life for mobility aid users?
22 hours ago ... Power wheelchair users who rely on their chair for daily commuting and want ... What decorative and functional personalization options exist for mobility aids?
