Identification of the deviation of seam tracking and weld cross type for the derusting of ship hulls using a wall-climbing robot based on three-line laser structural light

Abstract

To realize fully automatic rust removal from the large splicing weld of a ship hull section, we proposed a laser vision identification method based on three-line laser structural light. First, we calibrated the three-line laser vision sensor and obtained the internal and external parameters of the sensor and the laser plane equation of the three-line stripes. On this basis, to accurately obtain the feature points of the weld, we proposed a stepwise piecewise segmenting method for the laser stripe to approximate the true weld curve near the feature point, and we used a Freeman chain code method to mark the weld feature line to eliminate the abnormal points of the laser stripe. Furthermore, for the vertical and horizontal intersections of large splicing welds, we established a uniform recognition model of the cross-shaped or T-shaped weld based on the height characteristics of the three laser stripes and the distances between adjacent laser stripes. The experimental verification showed that the three-line laser method has better anti-interference ability and more abundant information, and it can accurately calculate the weld deviation and identify the cross-shaped or T-shaped weld types under various working conditions, which laid the foundation for real-time seam tracking and trajectory planning.