@misc {pub6462,
	title = {Attentive, Curious, and Aware: From LLMs to Action in Human-Robot Interaction},
	author = {Michael Gienger},
	year = {2025},
	month = {November},
	abstract = {The recent breakthroughs in Generative AI offer fantastic opportunities to research novel concepts for intelligent embodied agents. In this talk, I will introduce recent research in exploiting Large Language Models (LLMs) for robot task and motion planning. We combined reasoning, planning, and motion generation, and introduced a novel concept for correcting errors during planning and execution. I{\textquoteright}ll show several results both in simulations and real-world tasks for tasks like block arrangement, cocktail, and pizza preparation. I will then discuss our recent concept of {\textquotedblleft}Attentive Support{\textquotedblright}, in which we made the step from LLM-based autonomous problem-solving capabilities to human-robot group constellations and conclude with my view of interesting future research questions.},
	publisher = {Presentation only},
	booktitle = {International Workshop on AI FOR ROBOTICS}
}