Abstract: To improve the the autonomous navigation accuracy of the mobile chassis in greenhouse ridge cultivation mode, a combined navigation control system was innovatively developed for leafy vegetable ridges with poor straightness. The system mainly consists of a vision module, UWB module, and controller module. Firstly, a depth camera is used to capture images of the leafy vegetable ridge surface in front of the robot. The YOLOv8s seg algorithm is used to segment the leafy vegetable ridge surface, and the Canny algorithm is used to identify the ridge surface edges. Finally, the least squares method is used to extract visual navigation lines; A control segmentation line between UWB navigation and visual navigation was constructed for autonomous navigation and tracking of mobile robots in a monopolistic environment. A mobile navigation control strategy for crop protection robots based on UWB/visual combination was proposed, and a navigation tracking control model was established based on pure tracking algorithm; Finally, autonomous navigation experiments were conducted in actual field scenarios, and the results showed that when the crop protection machine was traveling at speeds of 0.4～0.5 m/s, the maximum tracking deviations of visual navigation and UWB navigation were 0.063 and 0.058 m, respectively, and the average errors were 0.047 and 0.043 m, respectively. Pure visual navigation and UWB navigation have smaller tracking errors, which verifies the feasibility of the navigation line extraction algorithm proposed in this paper and the reliability of UWB navigation, providing a foundation for the combination of the two. The boundary for integrated navigation control is 0.15 m, and the maximum tracking deviations for the two sets of integrated navigation experiments are 0.152 and 0.155 m, respectively, with average errors of 0.059 and 0.061 m, respectively. Through the analysis of experimental results, it can be concluded that UWB navigation control in integrated navigation has played a significant positive regulatory role in extreme situations, significantly reducing navigation deviation and deviation fluctuation. Therefore, combined navigation has improved navigation accuracy and robustness to a certain extent, providing technical support for improving agricultural production efficiency and developing precision agriculture.