Abstract: An end-effector is one of the most important components in the fruit picking robot. The picking mechanism of the end-effector can also dominate the picking efficiency. However, the picking end-effector with the fixed structure and parameters cannot fully meet the picking needs of different fruit diameter ranges, due to the wide variety of objects being picked at present. In this study, an underactuated articulated end-effector was designed, including four picking fingers. Each picking finger with two joints was driven by a connecting rod to simulate the human envelope-picking action. The hand with the intention of picking citrus was used to simulate a similar spherical fruit. The better performance of the end-effector was achieved in the small number of system drives, the low overall system complexity, and the small damage to the fruit during the picking process. A parametric design was also proposed using an improved genetic algorithm (GA), in order to improve the repetitive design of this type of end-effector. The picking range of fruit diameters was expanded to improve the feasibility of the movement. Microsoft Visual Studio 2012 development platform was utilized to customize the MFC design parameter interface. The end-effector structure was then previewed to input the initial parameters in the interface. The improved GA optimization was adopted to combine with the secondary development module NXOpen of NX. The parameters were assigned to the mechanism model in the form of expressions during optimization. Specifically, the structural parameters were optimized during this time. The end-effector was pre-modeled to fully meet the optimal picking conditions. Adams platform was employed to conduct the dynamic simulation analysis on the optimized grasping end-effector model. The maximum displacement offset of the optimized end-effector increased by about 29.1%. The optimal displacement value was achieved in the objective function. The simulation curve image was added into the parametric design system for display through the Python script. The correctness of the optimal design was then verified after simulation. A physical prototype was carried out indoor and orchard citrus picking experiments, according to the designed end-effector mechanism. In the laboratory environment, the success rate of envelope picking reached 100% for 20 citruses with a diameter in the range of 64-102 mm. The end-effector was connected to the self-made robotic arm. The end of the mechanical arm turned the end-effector "wrist" after the finger mechanism formed an envelope, and then twisted the fruit handle to complete the picking. Picking experiments were performed on the citrus with the different fruit diameters in the orchard. The test results show that the success rate of picking citrus with a diameter of 68-106 mm reached 92.9%. The displacement parameters of the optimized end-effector were measured to obtain the maximum displacement (61.4 mm) of the single-ended joint, similar to the Adams simulation. Since the maximum offset was set in the optimization objective function, there was a threshold for the maximum opening of the picking node, in order to reduce the interference of branches and leaves. The total success rate reached 92.9% in the picking test. The parametric design can realize the rapid deformation response of the end-effector to the spherical fruits with different fruit diameter ranges. GA was also used to optimize the working parameters of the mechanism, in order to improve the feasibility of picking and the accuracy of mechanism design.