Kiwifruit picking robots can replace manual labor for mechanized kiwifruit harvesting. However, existing picking robots encounter issues such as low separation efficiency of fruit stalks, poor stability of fruit gripping, and inaccurate identification when picking kiwifruit clusters. In response, a multi-fruit picking end-effector was designed to pick clusters of kiwifruit efficiently based on their distribution characteristics. The gripping range of the gripping device was determined based on the parameters of the spatial distribution of the fruit clusters. A multi-fruit gripping mechanics model was constructed, and the gripping force was analyzed to ensure efficient and stable fruit picking. Critical parameters of the fruit stalk separation device were determined through kinematic trajectory analysis to improve the separation efficiency of fruit stalks. Additionally, a dual-sensor fusion recognition method was proposed to identify fruit cluster locations accurately. The results of the picking experiment demonstrate that the end-effector can pick fruits in an average time of 8.28 s per cluster, with a net fruit-picking rate of 87.5% and a fruit damage rate of 7.5%. The end-effector shows a positive picking effect on kiwifruit fruits distributed in clusters. This study can serve as a reference for the development of kiwifruit-picking robots.