To address the problem of reduced operational efficiency of photovoltaic cleaning robots caused by inconvenient transportation in the desert area of Shago, an aerial transfer system for photovoltaic cleaning robots based on drones was proposed in this study. Initially, a near-infrared light source guide sign was designed, and the OPENMV module was employed for image recognition. The threshold segmentation method and edge recognition method were applied to construct a guide sign recognition algorithm, enhancing the positioning accuracy and anti-interference capability of the guide sign. Subsequently, a conical adsorption docking structure and a parallel symmetrical centering docking structure were designed to solve the docking issues between photovoltaic cleaning robots and drones under inclined conditions. A prototype of the drones and two docking platforms was then developed, and experiments were conducted on the visual positioning accuracy of drones and the transportation performance of the docking platforms. The experimental results indicate that the visual positioning error of drones remains within 10 cm, effectively reducing the external environment′s interference on the recognition effect. Both docking platforms adapt to docking operation requirements at photovoltaic panel inclination angles within 40 degrees, achieving a docking success rate consistently exceeding 90%, thereby meeting the operational requirements for stable docking and simple separation.