Aiming to solve the problems that most of manipulator grasping objects in the specified position and poor flexibility，a target detection algorithm based on deep learning was proposed to identify objects. Binocular vision algorithm was used to detect the spatial position of objects, and D-H method was used to solve the coordinate of manipulator, so the object grasping was realized. According to actual demand, target location detection was realized by combining the good real-time target detection algorithm YOLOv4 with the stereo matching algorithm SGBM in OpenCV, and the cloud server was rented to train the neural network and run programs,so the local hardware requirements was reduced. The experimental results show that the success rate of the manipulator grasping objects reaches 84%, which verifies that the method has good accuracy and basically meets the actual needs of intelligent manufacturing.