RESUMEN
To solve the problem of cumulative errors when robots build maps in complex orchard environments due to their large scene size, similar features, and unstable motion, this study proposes a loopback registration algorithm based on the fusion of Faster Generalized Iterative Closest Point (Faster_GICP) and Normal Distributions Transform (NDT). First, the algorithm creates a K-Dimensional tree (KD-Tree) structure to eliminate the dynamic obstacle point clouds. Then, the method uses a two-step point filter to reduce the number of feature points of the current frame used for matching and the number of data used for optimization. It also calculates the matching degree of normal distribution probability by meshing the point cloud, and optimizes the precision registration using the Hessian matrix method. In the complex orchard environment with multiple loopback events, the root mean square error and standard deviation of the trajectory of the LeGO-LOAM-FN algorithm are 0.45 m and 0.26 m which are 67% and 73% higher than those of the loopback registration algorithm in the Lightweight and Ground-Optimized LiDAR Odometry and Mapping on Variable Terrain (LeGO-LOAM), respectively. The study proves that this method effectively reduces the influence of the cumulative error, and provides technical support for intelligent operation in the orchard environment.
RESUMEN
OBJECTIVE: To explore the CD phenotypic, protein expression and pluripotent differentiation of human hypertrophic scar fibroblasts cultured in vitro, so as to study the mechanisms of scar formation. METHODS: Fibroblasts were isolated and cultured from human hypertrophic scar of 3 cases. The cells morphology was observed by inverted microscope, and the growing state of the third passage was detected by the cell counting meter of Vi-CELL. The cell surface markers CD105, CD14, CD73, CD34, CD44, CD45 and CD90 were identified by flow cytometry. The expression of CK19, Oct-4, Nanog and vimentin was detected by immunocytochemistry, and the expression of alpha-smooth muscle actin(alpha-SMA) was tested by immunofluorescence. The differentiated potential of fibroblasts of the third passage into adipogenic, osteogenic and chondrogenic lineages was assayed. RESULTS: The primary passage fibroblasts showed the shape of spindle shaped or irregular polygon with a radiated or circinate of growing arrangement. The growth curve showed the cells growth was slow on the first and second day, and quick during the third to fifth day, which reached platform stage on the sixth or seventh day. The fibroblasts highly expressed mesenchymal stem cell surface markers-CD73, CD105, CD44, CD90, but not expressed hematopoietic stem cell surface markers-CD14, CD34, CD45 by flow cytometry. And positive expression of vimentin, Oct-4 and negative expression of CK19 were detected by Immunocytochemistry. Positive expression of alpha-SMA was also detected by immunofluorescence. Multidirectional differentiation induction indicated that the third passage cells could differentiate into adipogenic, osteogenic and chondrogenic lineages. CONCLUSIONS: Human hypertrophic scar-derived fibroblasts show the biologic characteristics of mesenchymal stem cells, which may play an important role in wound healing and hypertrophic scar formation.