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Research on the Development Trends of Artificial Intelligence Robot Technology in the Elderly Care Sector

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DOI: 10.23977/jaip.2025.080202 | Downloads: 20 | Views: 588

Author(s)

Xuan Qin 1, Zilan Liu 1, Ke Huang 1, Tianxin Yang 1, Xinyao Lu 1, Yuxia Xi 1, Bin He 1

Affiliation(s)

1 School of Economics and Management, Taizhou University, Taizhou, China

Corresponding Author

Bin He

ABSTRACT

As global aging accelerates, artificial intelligence (AI) robotics is becoming an essential tool in improving the quality of life for the elderly. This paper explores the development trends of AI robotics in elderly care. It first analyzes the current state of technology, covering both global and Chinese application scenarios and development trends of elderly care robots. The study identifies key factors driving progress, such as intelligent perception and interaction, machine learning, adaptive technology, and human-robot collaboration with safety control. Further analysis suggests that future developments will focus on technological integration and innovation, the diversification and personalization of functions, and enhanced intelligence and autonomy. However, challenges remain, including technological barriers, ethical and legal concerns, and issues related to social acceptance and cultural adaptation. The paper proposes strategies to address these challenges, including promoting technological research and innovation, ensuring privacy protection, establishing industry policies and standards, and encouraging talent development and cross-disciplinary cooperation. These efforts aim to promote the sustainable development of AI robotics in elderly care, ultimately providing better services and support for the elderly population.

KEYWORDS

Artificial Intelligence; Robotics Technology; Elderly Care

CITE THIS PAPER

Xuan Qin, Zilan Liu, Ke Huang, Tianxin Yang, Xinyao Lu, Yuxia Xi, Bin He, Research on the Development Trends of Artificial Intelligence Robot Technology in the Elderly Care Sector. Journal of Artificial Intelligence Practice (2025) Vol. 8: 6-14. DOI: http://dx.doi.org/10.23977/jaip.2025.080202.

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