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Aiming at the problem that the current cherry tomato picking robot cannot guarantee the picking with pedicle, a method of analyzing the posture of cherry tomatoes through machine vision and then generating a specific picking action of the robotic arm is proposed; by simulating the manual picking process, this method can make the end effector of the robotic arm reach the picking position in line with the direction of the fruit pedicle of cherry tomatoes; the overall system includes the target detection of ripe cherry tomatoes, the realization of the distance measurement algorithm, the recognition of the direction of the cherry tomatoes, and the generation of robotic arm movements; according to the idea of contour fitting algorithm, the algorithm is improved to achieve a more accurate and stable direction recognition algorithm for cherry tomatoes, so as to obtain the target pose of the end effector of the robotic arm in the same direction as the saint fruit, and then realize the corresponding generation of robotic arm picking motions; multiple experiments have shown that the improved recognition algorithm for the direction of cherry tomatoes has a smaller error angle than the traditional contour fitting algorithm, and it is more stable for the direction recognition of cherry tomatoes in different postures, therefore, it is more suitable for the specific picking action of the robotic arm generated according to the posture of cherry tomatoes in the actual picking process.