In this paper,we present a novel surface mesh generation approach that splits B-rep geometry models into isotropic triangular meshes based on neural networks and splitting lines.In the first stage,a recursive method i...In this paper,we present a novel surface mesh generation approach that splits B-rep geometry models into isotropic triangular meshes based on neural networks and splitting lines.In the first stage,a recursive method is designed to generate plentiful data to train the neural network model offline.In the second stage,the implemented mesh generator,ISpliter,maps each surface patch into the parameter plane,and then the trained neural network model is applied to select the optimal splitting line to divide the patch into subdomains continuously until they are all triangles.In the third stage,ISpliter remaps the 2D mesh back to the physical space and further optimizes it.Several typical cases are evaluated to compare the mesh quality generated by ISpliter and two baselines,Gmsh and NNW-GridStar.The results show that ISpliter can generate isotropic triangular meshes with high average quality,and the generated meshes are comparable to those generated by the other two software under the same configuration.展开更多
In order to make the humanoid robot walk freely in complicated circumstance, the reliable capabilities for obtaining plane information from its surroundings are demanded. A system for extracting planes from data taken...In order to make the humanoid robot walk freely in complicated circumstance, the reliable capabilities for obtaining plane information from its surroundings are demanded. A system for extracting planes from data taken by stereo vision was presented, After the depth image was obtained, the pixels of each line were scanned and split into straight line segments. The neighbouring relation of line segments was kept in link structure. The groups of three line segments were selected as seed regions. A queue was maintained for storing seed regions, and then the plane region was expanded around the seed region. The process of region growing continued until the queue of seed regions was empty. After trimming, the edges of the planes became smooth. In the end, extracted planes were obtained. In the experiment, two models were used： pipe and stairs. Two planes in pipe mode/and six planes in stairs model were extracted exactly. The speed and precision of algorithm can satisfy the demands of humanoid robot＇s navigation.展开更多
基金the National Key Research and Development Program of China(No.2021YFB0300101)the National Natural Science Foundation of China(Nos.12102467 and 12102468)+1 种基金the Foundation of National University of Defense Technology(No.ZK21-02)the Foundation of State Key Laboratory of High Performance Computing of China(Nos.202101-01 and 202101-19).
文摘In this paper,we present a novel surface mesh generation approach that splits B-rep geometry models into isotropic triangular meshes based on neural networks and splitting lines.In the first stage,a recursive method is designed to generate plentiful data to train the neural network model offline.In the second stage,the implemented mesh generator,ISpliter,maps each surface patch into the parameter plane,and then the trained neural network model is applied to select the optimal splitting line to divide the patch into subdomains continuously until they are all triangles.In the third stage,ISpliter remaps the 2D mesh back to the physical space and further optimizes it.Several typical cases are evaluated to compare the mesh quality generated by ISpliter and two baselines,Gmsh and NNW-GridStar.The results show that ISpliter can generate isotropic triangular meshes with high average quality,and the generated meshes are comparable to those generated by the other two software under the same configuration.
基金Project(60776816) supported by the National Natural Science Foundation of China and Civil Aviation Administration of ChinaProject(8251064101000005) supported by the Natural Science Foundation of Guangdong Province,China
文摘In order to make the humanoid robot walk freely in complicated circumstance, the reliable capabilities for obtaining plane information from its surroundings are demanded. A system for extracting planes from data taken by stereo vision was presented, After the depth image was obtained, the pixels of each line were scanned and split into straight line segments. The neighbouring relation of line segments was kept in link structure. The groups of three line segments were selected as seed regions. A queue was maintained for storing seed regions, and then the plane region was expanded around the seed region. The process of region growing continued until the queue of seed regions was empty. After trimming, the edges of the planes became smooth. In the end, extracted planes were obtained. In the experiment, two models were used： pipe and stairs. Two planes in pipe mode/and six planes in stairs model were extracted exactly. The speed and precision of algorithm can satisfy the demands of humanoid robot＇s navigation.
