Intelligent plant protection machinery in large fields is an important means to improve pesticide utilization, enhance the quality of agricultural products, and ensure the sustainable development of agriculture. In order to understand the research status of intelligent plant protection technology and clarify the future development direction, this article focused on three main directions of intelligent operation of high-clearance plant protection machinery: prescription application in large-scale farmland, target spraying on a small scale in land parcels, and variable-speed spraying. From the aspects of perception, analysis, decision-making, and control, the article elaborates on the technical principles of prescription map construction, spatial coordinate transformation methods, and prescription recognition that integrate high-precision satellite positioning, the current level of key technologies for target spraying technology routes and weed recognition, and believed that high-precision spraying based on online prescriptions must be the focus of future research. The article carried out a comparative analysis of the advantages and disadvantages of four speed measurement modes for variable-speed spraying and believed that with the widespread application of satellite positioning in agricultural machinery, satellite-based speed measurement will become the main method of high-precision speed measurement due to its greater versatility, convenience, and accuracy. To explore the current development status of variable spraying control, the article summarized two control methods and implementation methods for pressure-controlled variable spraying. From a comprehensive perspective, pipeline cut-off flow control is the main way to achieve variable spraying, and three control algorithms of segmented control, pulse width modulation, and PID control of flow control were analyzed from the perspective of technical principles, implementation processes, and optimized applications. After the discussion, it is believed that PID control based on machine learning will be an important direction to improve traffic control performance. With the continuous development of artificial intelligence technology, plant protection robots that integrate intelligent perception, analysis and decision-making and autonomous operation capabilities will become the mainstream development direction of plant protection machinery in the future.