Research Statutes and Prospects of AI in Domestic Robot Manufacturing

DOI

10.2991/978-94-6463-518-8_67How to use a DOI?

Keywords

Domestic robot; AI; Deep learning

Abstract

In the past few years, the field of artificial intelligence (AI) has experienced explosive growth. Large language models (LLM) such as some AI developed for chat and information generation have drawn massive attention from the public, and more robots for commercial uses are implemented with them. However, from recent research reports, the development of domestic robots seems to be relatively slow, and the achievements are insignificant. The most common domestic robot in households is still the sweeping robot, which lacks an AI system inside. Therefore, this paper discusses the current developments of domestic robots, the principle of deep learning, the applications of AI in domestic robots as well as their benefits. This paper summarizes the existing development of domestic robots, the principle and applications of AI inside domestic robots, pointing out a possible direction of utilizing AI with deep learning for future domestic robots’ development. With the ability to think independently, future domestic robots will be able to carry out complex moves and logical thinking, enabling them to not only complete complex household chores with ease, but also provide linguistic interactions and many other functions.

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.

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TY  - CONF
AU  - Linhao Fan
AU  - Siyi Ruan
PY  - 2024
DA  - 2024/09/28
TI  - Research Statutes and Prospects of AI in Domestic Robot Manufacturing
BT  - Proceedings of the 2024 International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2024)
PB  - Atlantis Press
SP  - 704
EP  - 713
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-518-8_67
DO  - 10.2991/978-94-6463-518-8_67
ID  - Fan2024
ER  -