The invention discloses a generative confrontation network-based method for writing calligraphy by a robot and relates to the robot. The method comprises the steps of collecting standard calligraphy stroke data, collating and sorting according to stroke types and making annotations; training two deep neural networks: a generative network G and a confrontation network D, on the basis of a generative confrontation network model; inputting a randomly sampled vector into the generative network G to obtain the probability distribution of track points of strokes; obtaining position information of the strokes from the probability distribution by adopting a sampling method and writing the strokes to a drawing board by a calligraphic robot and shooting and recording images of the strokes by a camera after the writing; and preprocessing the to-be-processed images and inputting into the confrontation network D to train and adjusting parameters to achieve convergence. The generation mechanism hasa good learning ability to enable the calligraphic robot to have a generation mechanism that can automatically generate various styles of strokes, so that the difficulty that a large number of labor power is consumed to manually input, of a current calligraphic robot, is solved.