Abstract: A robot welding method based on semantic feature clustering; the method comprises: acquiring an image of a workpiece, and generating an image training sample set; performing semantic annotation on the image of the workpiece to generate a semantic training sample set; establishing a semantic clustering model, and training same by using the image training sample set and the semantic training sample set; by using the trained semantic clustering model, identifying an image of a workpiece to be welded, so as to obtain data of the workpiece to be welded; on the basis of the data of the workpiece to be welded and by using parameterized online programming, generating a welding program for the workpiece to be welded; and on the basis of the welding program, executing welding of the workpiece to be welded. By means of the robot welding method based on semantic feature clustering, neither teaching programming nor offline programming is required, thereby improving the precision, efficiency, universality and flexibility.

Abstract: The present invention provides a breeding method of a new variety of hard-shelled razor clams, comprising the following steps: a. Estimating the heritability of shell hardness trait: constructing full-sib families to estimate the heritability of the growth and shell hardness traits of the razor clams; b. Selecting individuals with hard shells from basic population using an electronic hardness tester of material mechanics as the broodstock clams; c. Artificially-induced spawning; d. The offspring grow-out; e. Purification of the new strain: with the new strain of hard-shelled generation 1 adults obtained in step d as broodstocks, repeating the steps c and d several times to obtain a new variety of razor clams with hard shells, and the shell hardness trait of razor clams has stable heritability.