3D curvature grinding path planning based on point cloud data

Abstract

This paper proposes a novel method which uses online measurement data to create robot path for 3D grinding of workpieces with complex surfaces. The surface is measured as point cloud by a 3D scanner. The point cloud data is processed by filtering and smoothing, and then used for path planning. The grinding paths are generated by creating a series of planes to intersect with the target surface. A point cloud data slicing algorithm based on octree is developed to calculate the intersecting lines between point cloud data and planes. Subsequently the equal step method developed discretizes the grinding path for smooth curvatures, and utilizes local plane fitting to estimate the normal at contact points.