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LLM-Driven Augmented Reality Puppeteer: Controller-Free Voice-Commanded Robot Teleoperation

Yuchong Zhang, Bastian Orthmann, Michael C. Welle, Jonne Van Haastregt, Danica Kragic

Year
2025
Access
Open access

Abstract

The integration of robotics and augmented reality (AR) presents transformative opportunities for advancing human-robot interaction (HRI) by improving usability, intuitiveness, and accessibility. This work introduces a controller-free, LLM-driven voice-commanded AR puppeteering system, enabling users to teleoperate a robot by manipulating its virtual counterpart in real time. By leveraging natural language processing (NLP) and AR technologies, our system -- prototyped using Meta Quest 3 -- eliminates the need for physical controllers, enhancing ease of use while minimizing potential safety risks associated with direct robot operation. A preliminary user demonstration successfully validated the system's functionality, demonstrating its potential for safer, more intuitive, and immersive robotic control.

Keywords

cs.HCcs.RO

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