Point cloud registration is an important issue in 3D information processing. The traditional point cloud registration needs a huge amount of computation, thus it is not suitable for real-time and mobile computation. In order to solve the problem of traditional point cloud registration method, a method based on convolutional neural network is proposed. The depth image of point cloud is calculated and the differential feature vector of depth images extracted by the convolutional neural network is regarded as input of fully connected neural network to calculate registration parameters. Iteratively executing the above process until registration error is acceptable. Experimental results show that the point cloud registration based on convolutional neural network is simpler in computation, more efficient in registration rate, and less sensitive to noise and outlier than the traditional methods.