The pineapple （Ananas comosus （L.） Merr.） picker with integrated clip needs to independently determine the cutting points in fruit stem of pineapple when picking in the field. Pineapple stems are easily obstructed by plant leaves and bracts， making it difficult to accurately identify the cutting points in fruit stem with a single method of image processing. A method for detecting the cutting points in fruit stem of pineapple based on the fusion of multi-sensor information was proposed. The length from the top of the pineapple crown bud to the bottom of the fruit was measured by combining a depth camera with multiple sets of photoelectric sensors and utilizing an improved YOLOv5 object detection algorithm to fuse RGB-D depth information. The changes in signal of photoelectric sensor were used to determine whether the pineapple picker has reached the top position of the crown bud. The top of the crown bud was used as the starting position to control the descent speed and time of the picker to ensure that the cutting blade installed at the bottom of the picker accurately reaches the cutting point of the fruit stem. The results of bench test showed that this method had a success rate of 85% in detecting the cutting points in real fruit stem of pineapple， meeting the accuracy requirements of detecting the cutting points in fruit stem of pineapple during the operation of pineapple picking robots. It will be of great significance for realizing the intelligent pineapple picking， and will lay a foundation for the subsequent development of pineapple picking robots in the field.