MARCER: Multimodal Augmented Reality for Composing and Executing Robot Tasks

In this work, we combine the strengths of humans and robots by developing MARCER, a novel interactive and multimodal end-user robot programming system. MARCER utilizes a Large Language Model to translate users' natural language task descriptions and environmental context into Action Plans for r...

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Vydané v:	2025 20th ACM/IEEE International Conference on Human-Robot Interaction (HRI) s. 529 - 539
Hlavní autori:	Ikeda, Bryce, Gramopadhye, Maitrey, Nekervis, LillyAnn, Szafir, Daniel
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 04.03.2025
Predmet:	Augmented reality End-user Robot Programming Human-Robot Collaboration Human-robot interaction Large language models Natural language processing Real-time systems Refining Robot programming Translation Usability Visualization
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