Patent ID: 11861793
Assignee: HUNAN UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 8:
9. The method for merging the surface skin three-dimensional data according to claim 8, wherein step S400 specifically comprises the following steps:
step S410: for each measuring point xi in the point cloud X, calculating the static closest distance from the measuring point xi to the point yi′, wherein three forms of distances, namely the Euclidean distance di_e0=∥xi−yi′∥, the normal distance di_n0=(xi−yi′)T ni′, and a distance di_r0 considering neighborhood feature reconstruction are comprised, and the distance of the neighborhood feature reconstruction is the surface adaptive distance,
where when a neighborhood of xi is a concave surface, di_r0=ri′−√{square root over (ri′×ri′−2ri′di_n0+di_e0×di_e0)}, and
when the neighborhood of xi is a convex surface, di_r0=√{square root over (ri′×ri′−2ri′di_n0+di_e0×di_e0)}−ri′; and
step S420: for each measuring point xi in the point cloud X, calculating the dynamic closest distance from the measuring point xi to the point cloud Y, defining a 6×1 differential motion screw as ξ, wherein the updated position is xi+=xie[ξ] when the differential motion screw ξ is provided at the measuring point xi, and calculating the dynamic closest distance from the measuring point xi+ to the point cloud Y, wherein three forms of distances, namely the Euclidean distance, the normal distance, and the distance considering the neighborhood feature reconstruction are comprised; wherein the dynamic Euclidean distance is expressed as di_e=∥xi−yi′+Eiξ∥ where Ei=[I3×3,−{circumflex over (x)}i] is a 3×6 coefficient matrix, I3×3 represents a 3×3 unit matrix, and {circumflex over (x)}i represents an antisymmetric matrix of the point xi, wherein the dynamic normal distance is expressed as di_n=di_n0+Niξ, where Ni=[niT,(xi×ni)T] is a 1×6 coefficient matrix,
where a dynamic distance of a convex surface considering the neighborhood feature reconstruction is di_r=√{square root over (ri′×ri′−2ri′di_n+di_e2)}−ri′, and
where a dynamic distance of a concave surface considering the neighborhood feature reconstruction is di_r=ri′−√{square root over (ri′×ri′−2ri′di_n+di_e2)}.