Design and research of agricultural underwater robots based on artificial intelligence algorithms

Zhaojun Huang

doi:10.63313/JCSFT.9023

Authors

Zhaojun Huang Zhuhai City Polytechnic, Zhuhai Guangdong, 519000, China Author

DOI:

https://doi.org/10.63313/JCSFT.9023

Keywords:

artificial intelligence, agricultural underwater robots, algorithm design, environmental perception, path planning

Abstract

With the rapid development of artificial intelligence technology, its application in the agricultural field has gradually become a research hotspot. This paper focuses on the design and research of agricultural underwater robots based on artificial intelligence algorithms, aiming to explore an intelligent system that can efficiently and accurately complete underwater agricultural tasks. The introduction of artificial intelligence algorithms can significantly improve the autonomous decision-making ability and environmental perception level of underwater robots. This paper first analyzes the characteristics of the agricultural underwater environment and the shortcomings of existing underwater robot technology, and clarifies the background and significance of this study. Subsequently, the basic principles of artificial intelligence algorithms and their application potential in underwater robots are introduced, and an algorithm model suitable for underwater operations is constructed based on the needs of agricultural scenarios. In terms of algorithm design, this paper adopts the method of combining deep learning and reinforcement learning to optimize the performance of the algorithm through data collection and processing, and improve the recognition and decision-making ability of underwater robots in complex environments. At the same time, in view of the problem of limited underwater communication, an efficient communication and control mechanism is designed to ensure the stable operation of the system. Finally, the integration and testing of the underwater robot system is completed, including hardware platform construction, software system development and environmental simulation testing, which verifies the feasibility and effectiveness of the system in practical application scenarios. Experimental results show that agricultural underwater robots based on artificial intelligence algorithms can achieve precise operations in different underwater environments, with good adaptability and stability, providing new technical support for the development of smart agriculture in the future.

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