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Main Authors: Zhou, Linkun, Li, Jian, Mo, Yadong, Zhang, Xiangyan, Zhang, Ying, Wei, Shimin
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2502.19706
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author Zhou, Linkun
Li, Jian
Mo, Yadong
Zhang, Xiangyan
Zhang, Ying
Wei, Shimin
author_facet Zhou, Linkun
Li, Jian
Mo, Yadong
Zhang, Xiangyan
Zhang, Ying
Wei, Shimin
contents Autonomous interaction is crucial for the effective use of elderly care robots. However, developing universal AI architectures is extremely challenging due to the diversity in robot configurations and a lack of dataset. We proposed a universal architecture for the AI-ization of elderly care robots, called AoECR. Specifically, based on a nursing bed, we developed a patient-nurse interaction dataset tailored for elderly care scenarios and fine-tuned a large language model to enable it to perform nursing manipulations. Additionally, the inference process included a self-check chain to ensure the security of control commands. An expert optimization process further enhanced the humanization and personalization of the interactive responses. The physical experiment demonstrated that the AoECR exhibited zero-shot generalization capabilities across diverse scenarios, understood patients' instructions, implemented secure control commands, and delivered humanized and personalized interactive responses. In general, our research provides a valuable dataset reference and AI-ization solutions for elderly care robots.
format Preprint
id arxiv_https___arxiv_org_abs_2502_19706
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle AoECR: AI-ization of Elderly Care Robot
Zhou, Linkun
Li, Jian
Mo, Yadong
Zhang, Xiangyan
Zhang, Ying
Wei, Shimin
Human-Computer Interaction
Robotics
Autonomous interaction is crucial for the effective use of elderly care robots. However, developing universal AI architectures is extremely challenging due to the diversity in robot configurations and a lack of dataset. We proposed a universal architecture for the AI-ization of elderly care robots, called AoECR. Specifically, based on a nursing bed, we developed a patient-nurse interaction dataset tailored for elderly care scenarios and fine-tuned a large language model to enable it to perform nursing manipulations. Additionally, the inference process included a self-check chain to ensure the security of control commands. An expert optimization process further enhanced the humanization and personalization of the interactive responses. The physical experiment demonstrated that the AoECR exhibited zero-shot generalization capabilities across diverse scenarios, understood patients' instructions, implemented secure control commands, and delivered humanized and personalized interactive responses. In general, our research provides a valuable dataset reference and AI-ization solutions for elderly care robots.
title AoECR: AI-ization of Elderly Care Robot
topic Human-Computer Interaction
Robotics
url https://arxiv.org/abs/2502.19706