The invention belongs to the field of industrial robots, and discloses an industrial robot constant-force grinding and polishing method based on big data. The method comprises the following steps of firstly, collecting robot running data, specifically, a six-component force sensor is connected with an industrial robot and a controller, and through continuous adjusting of the laminating degree of the same grinding track, a large amount of running data are collected for forming a training set; secondly, determining a BP neural network topological model; thirdly, according to the running data obtained in the first step, training the BP neural network topological model built in the second step; and fourthly, applying the trained BP neural network topological model to the grinding living example of the industrial robot without a sensor, obtaining a grinding force time domain curve in the running process of the industrial robot, and according to the preset grinding force threshold value, adjusting the track of the industrial robot, and obtaining the constant-force grinding effect. The path fine adjusting work is repeated, and the problems that grinding and polishing efficiency is low, and machining cost is high are solved.