Abstract: Abstract: Agriculture is crucial for economic development. Losses in agricultural production were caused by a variety of circumstances, but pests and illnesses are among the most important. The use of plant protection machinery to spray pesticides is still the most effective method of pest control at present. Traditional agricultural sprayers were inefficient and time-consuming, which caused pesticide waste and environmental contamination. In the process of spraying pesticides, farmers are directly exposed to pesticides, which is easy to cause bodily harm or even poisoning. With the steady progress of China's agricultural modernization, robots are widely used in agricultural plant protection work. Intelligent pesticide spraying robots are an effective method to solve the problem of applying pesticides in complex environments such as hills, orchards, fields, and greenhouses, which is more efficient and accurate. Intelligent spraying robot not only saves labor but also reduces the improper use of resources and environmental pollution. It is conducive to our better reaching of the goal of agricultural sustainable development. In this study, the research progress analysis of an intelligent pesticide spraying robot focuses on four respects: mobile chassis design, spraying the device design, navigation technology, and target detection technology. This paper discusses the factors limiting the development of intelligent pesticide-spraying robots for the primary technologies applied to various operation scenarios. Firstly, the mobile chassis design of the spraying robot was analyzed from the ground spraying robot and aerial spraying robot. The study and development of wheel-track composite robot chassis can integrate the advantages of wheeled chassis as well as a tracked chassis, which will be the research trend of ground intelligent spraying robot. Plant protection UAV is unrestricted by terrain, and can be applied to a variety of scenarios, which will be the key orientations for future research. Secondly, the spray devices required by the spraying robot in different spraying scenarios were summarized. It mainly includes an adjustable boom sprayer device, electrostatic spraying device, targeted spraying device, air-assisted spraying equipment, and profile modeling spray equipment. The most commonly used navigation methods are analyzed, including Global Positioning System (GPS) navigation, visual navigation, inertial navigation, multi-sensor fusion navigation, laser radar navigation, odometer, geomagnetic navigation, etc. Additionally, the detection methods of various pesticide spraying robots are evaluated from the perspectives of crop detection and pest detection. The deep learning algorithm can automatically extract the image features of crops, make use of the information, and exactly identify the location of crop pests and diseases, to quickly respond to achieve accurate spraying. Finally, the development trend of intelligent pesticide application robots for precise application is presented. Six requirements or prospects were proposed for the intelligent pesticide spraying robot development in the future, including to improve the response speed of the spraying robot, to improve detection accuracy, to design lightweight chassis, to reduce the development cost of the spraying robot, and to integrated air-ground spraying technology. In conclusion, intelligent and precise application robots have the potential to significantly improve the quality of precision agriculture operations by facilitating intelligent decision-making on operational parameters before actual operation.