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This is a Experimental Study study.

October 13, 2025Open Access

From Vague Instructions to Task Plans: A Feedback-Driven HRC Task Planning Framework based on LLMs

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LLMs effectively adapt task plans from vague human inputs, enhancing collaborative efficiency in human-robot interactions.
Dynamic task planning yielded better outcomes, allowing for real-time adjustments based on user feedback and preferences.
The hybrid framework proposed integrates feedback mechanisms, ensuring plans align with human intentions and context.
Incorporating concise prompts eliminates the need for lengthy instructions, facilitating easier adoption across diverse applications.

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This framework leverages large language models to enhance planning amid vague human instructions, suggesting improved collaboration.

Shervedani et al. (2025) studied this question.

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