The Future of the Smart Home: A Study of AI-based Automation for Home Robots
- DOI
- 10.2991/978-94-6463-518-8_65How to use a DOI?
- Keywords
- Artificial Intelligence; Household Robots; Autonomous Systems
- Abstract
As one of the emerging robotics directions, with the advancement of AI technology and the improvement of various algorithmic models, domestic service robots have begun to enter thousands of households. In this article, the author first uses specific data to show the huge potential of today's domestic service robot market, and then takes CAESAR, a domestic service robot, as an example, to briefly describe the combination of domestic service robots and AI, and how AI can help robots to make decisions in certain specific scenarios at home. The article also describes in detail the three main models of AI: large-scale language model, visual model, and speech recognition model, and their applications in different fields such as education, medicine, biology, and so on, as well as in people's daily lives. With the help of research on Chatgpt in the medical field, the article also discusses its near-passing performance in USMEL. With the advancement of technology, the development of AI and robotics is filled with various opportunities as well as difficulties and challenges.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Mingdian Yang PY - 2024 DA - 2024/09/28 TI - The Future of the Smart Home: A Study of AI-based Automation for Home Robots BT - Proceedings of the 2024 International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2024) PB - Atlantis Press SP - 675 EP - 687 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-518-8_65 DO - 10.2991/978-94-6463-518-8_65 ID - Yang2024 ER -