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.
@article{arxiv.2502.19706,
title = {AoECR: AI-ization of Elderly Care Robot},
author = {Linkun Zhou and Jian Li and Yadong Mo and Xiangyan Zhang and Ying Zhang and Shimin Wei},
journal= {arXiv preprint arXiv:2502.19706},
year = {2025}
}