Aiming at the current manual operation of the kilogram weight verification process, there are problems of low verification efficiency, high labor intensity, and low degree of automation. This paper proposes a real-time recognition and spatial positioning technology for the weight handle of stacked kilogram weights. First, the Faster R-CNN target detection method is used to realize the identification and positioning of the weight and the weight handle; according to the identified pixel point coordinates of the weight handle, the depth value information of the weight handle is obtained correspondingly. Preliminary experiments show that the method in this paper can realize the real-time recognition and positioning of the weight handle of the stacked kilogram group. The average accuracy of the boundary box recognition of the weight handle is 98.5%, and the time to acquire the image and identify the spatial coordinates of the weight in a single time does not exceed 0.473 s, the accuracy of weight handle recognition in multiple experiments is 100%, which meets the real-time identification and positioning requirements of the weight handle of the stacked kilogram group.