The invention relates to the technical field of
logistics automation, in particular to a full-automatic stacking method and
system based on
machine vision and path planning, and the method comprises the following steps: based on three-dimensional
point cloud data of goods, extracting
point cloud coordinates, normal vectors and curvature values of the surface of the goods, calculating the geometric segmentation range of
point cloud edge features, and calculating the geometric segmentation range of the point cloud edge features; and calculating a fitting relationship between the boundary size and curvature distribution. According to the method, the
surface point cloud coordinates, the normal vector and the curvature value are extracted based on the three-dimensional point
cloud data, the accuracy of geometric
feature description of the complex cargo surface is enhanced, the geometric center and the variance range are reasonably determined through
spatial distribution analysis and
feature set classification, the accuracy and stability of shape classification are improved, and the accuracy and stability of shape classification are improved through
gravity center and size deviation calculation. The position and pressure distribution of the contact point are optimized, the space priority analysis of the grabbing point and the obstacle point is combined, the path planning and obstacle point
elimination strategy is optimized, the path conflict is reduced, and the flexibility and efficiency of logistics operation are improved.