Robot Operation of Home Appliances by Reading User Manuals

Fuente: arXiv
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Autori principali: Zhang, Jian, Zhang, Hanbo, Xiao, Anxing, Hsu, David
Natura: Preprint
Pubblicazione: 2025
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author Zhang, Jian
Zhang, Hanbo
Xiao, Anxing
Hsu, David
author_facet Zhang, Jian
Zhang, Hanbo
Xiao, Anxing
Hsu, David
contents Operating home appliances, among the most common tools in every household, is a critical capability for assistive home robots. This paper presents ApBot, a robot system that operates novel household appliances by "reading" their user manuals. ApBot faces multiple challenges: (i) infer goal-conditioned partial policies from their unstructured, textual descriptions in a user manual document, (ii) ground the policies to the appliance in the physical world, and (iii) execute the policies reliably over potentially many steps, despite compounding errors. To tackle these challenges, ApBot constructs a structured, symbolic model of an appliance from its manual, with the help of a large vision-language model (VLM). It grounds the symbolic actions visually to control panel elements. Finally, ApBot closes the loop by updating the model based on visual feedback. Our experiments show that across a wide range of simulated and real-world appliances, ApBot achieves consistent and statistically significant improvements in task success rate, compared with state-of-the-art large VLMs used directly as control policies. These results suggest that a structured internal representations plays an important role in robust robot operation of home appliances, especially, complex ones.
format Preprint
id arxiv_https___arxiv_org_abs_2505_20424
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Robot Operation of Home Appliances by Reading User Manuals
Zhang, Jian
Zhang, Hanbo
Xiao, Anxing
Hsu, David
Robotics
Artificial Intelligence
Systems and Control
Operating home appliances, among the most common tools in every household, is a critical capability for assistive home robots. This paper presents ApBot, a robot system that operates novel household appliances by "reading" their user manuals. ApBot faces multiple challenges: (i) infer goal-conditioned partial policies from their unstructured, textual descriptions in a user manual document, (ii) ground the policies to the appliance in the physical world, and (iii) execute the policies reliably over potentially many steps, despite compounding errors. To tackle these challenges, ApBot constructs a structured, symbolic model of an appliance from its manual, with the help of a large vision-language model (VLM). It grounds the symbolic actions visually to control panel elements. Finally, ApBot closes the loop by updating the model based on visual feedback. Our experiments show that across a wide range of simulated and real-world appliances, ApBot achieves consistent and statistically significant improvements in task success rate, compared with state-of-the-art large VLMs used directly as control policies. These results suggest that a structured internal representations plays an important role in robust robot operation of home appliances, especially, complex ones.
title Robot Operation of Home Appliances by Reading User Manuals
topic Robotics
Artificial Intelligence
Systems and Control
url https://arxiv.org/abs/2505.20424