Abstract
Greenhouse cultivation promotes an efficient and environmentally friendly agricultural production model, significantly enhancing resource sustainability and advancing sustainable agriculture. Traditional greenhouse pollination methods are inefficient and labor-intensive, limiting the economic benefits of greenhouse pear cultivation. To improve pollination efficiency and achieve fully automated mechanized operations, an innovative design method for greenhouse pear pollination drones has been developed. First, design criteria were extracted using Grounded Theory (GT), and the Analytic Hierarchy Process (AHP) was employed to determine the weight of user demand evaluation indicators. Next, the Quality Function Deployment (QFD) method translated user needs into technical requirements, resulting in the final ranking of design element weights. The drone was then designed based on these weighted rankings, yielding an optimal solution. This method quantifies the functional requirements of the product, effectively identifying key needs for the greenhouse pear pollination drones and proposing targeted solutions. Additionally, it provides a design reference for other highly functional agricultural machinery products.