Traditional manual grinding of free edges of ship structural components has low efficiency

long cycle

and is harmful to the health of operators.Research on the machine vision-based grinding robot path planning algorithm for industrial robotic arm to automatically grind ship components is carried out.Firstly

3D point cloud data are used to generate grayscale images.Relying on the mapping relationship between grayscale images and point cloud data

the robot grinding path is obtained by processing grayscale images

which reduces the complexity of the algorithm processing.Secondly

the"snake sorting"algorithm is designed to optimize the sorting of Canny edge detection results

yielding a continuous and non-repeating grinding path.Finally

simulation calculation is carried out.The results show that the system has a maximum error of 1.108mm on straight paths and 1.371mm on curved paths

which can meet the free-edge grinding requirements of ship structural components.