关键词: 增材制造, 曲线重建, 点云分层, 非监督神经网络

Abstract: For slice 3D point cloud,the building of consecutive slices was interpreted as animated curves tracing,and an unsupervised neural network was proposed,which incrementally reconstructed curves from scattered points.The solution firstly re-sampled point cloud by slicing plane to yield 2D samples,and then presented them to the network in succession for growing,shrinking,moving and reconnecting dynamically,which extracted local principal components and topologies of samples.Upon convergence on one slice,the network represented several polylines as current slice output.Meanwhile,those polylines served as initial estimation for next slice.The re-sampling-learning routine iterated overall subsequent slices to construct them incrementally.Compared with existing non-incremental approaches,the proposed solution could accelerate point cloud slicing taking advantage of shape coherence between finely spaced slices and reconstruct hundreds or thousands of topologically correct slices without user intervention.

Key words: additive manufacturing, curve reconstruction, point cloud slicing, unsupervised neural network