Disclosed is a localization method based on deep learning, the method comprising: constructing a basic convolutional neural network, and extracting, by means of the basic convolutional neural network, a deep learning feature of an acquired image; constructing a region proposal network, screening a preliminary candidate anchor box to determine foreground and background labels, and calculating an offset between label data and the screened anchor box; according to the feature mapping output by the basic convolutional neural network, generating a rotated rectangular local candidate box, wherein the rotated rectangular local candidate box is represented by using coordinates of two fixed points and a height; and according to the intersection-over-union of a rotated rectangle of the rotated rectangular local candidate box, screening a candidate region, calculating a classification loss, predicting the coordinate and angle losses of the rotated box, and obtaining optimal model parameters, and thereby carrying out localization. Angle information of a target can be recognized, and a rotated localization box can assist a manipulator in grabbing a target more accurately.
LOCALIZATION METHOD AND SYSTEM BASED ON DEEP LEARNING