We present a method to design the deformation behavior of 3D printed models by an interactive tool, where the variation of bending elasticity at different regions of a model is realized by a change ...in shell thickness. Given a soft material to be used in 3D printing, we propose an experimental setup to acquire the bending behavior of this material on tubes with different diameters and thicknesses. The relationship between shell thickness and bending elasticity is stored in an echo state network using the acquired dataset. With the help of the network, an interactive design tool is developed to generate non‐uniformly hollowed models to achieve desired bending behaviors. The effectiveness of this method is verified on models fabricated by different 3D printers by studying whether their physical deformation can match the designed target shape.
A flattenable mesh surface is a polygonal mesh surface that can be unfolded into a planar patch without stretching any polygon. This paper presents a new method for computing a slightly stretched ...flattenable mesh surface
M
from a piecewise-linear surface patch
P
∈
R
3
, where the shape approximation error between
M
and
P
is minimized and the strain of stretching on
M
is controlled. Prior approaches result in either a flattenable surface that could be quite different from the input shape or a (discrete) developable surface has relative simple shape. The techniques investigated in this paper overcome these difficulties. First, we introduce a new surface modeling method to conduct a sequence of nearly isometric deformations to morph a flattenable mesh surface to a new shape which has a better approximation of the input surface. Second, in order to get better initial surfaces for fitting and overcome topological obstacles, a shape perturbation scheme is investigated to obtain the optimal surface fitting result. Last, to improve the scalability of our optimal surface fitting algorithm, a coarse-to-fine fitting framework is exploited so that very dense flattenable mesh surfaces can be modeled and boundaries of the input surfaces can be interpolated.
We provide a flexible shape control technique in this paper for the automatic resizing of apparel products. The automatic resizing function has become an essential part of the 3D garment CAD systems ...to generate user customized apparel products for individuals with variant body shapes. The human bodies are usually represented by piecewise linear mesh surfaces with consistent connectivity. The shape of apparel products can then be warped from the space around a human body to the space around another body by computing the new positions of points on apparel products. However, one major limitation of this kind of automatic resizing technique is that the apparel products are always distorted along the shape of the human bodies. This is a required deformation for tight clothes but not an expected result for other types of clothes. To solve this problem, we investigate a method to preserve the shape of user-defined features on the apparel products. As the apparel products are often represented by discrete surfaces with non-manifold entities, the existing mesh processing approaches that preserve the local shape cannot be applied here. A new algorithm consisting of three steps is developed in this paper. First, the apparel product is warped from the reference human body to the space around the target human body. Second, the shape of features is optimized to match their original shape before the warping. Lastly, discrete surfaces of the apparel product are deformed again under an optimization framework to match their original shapes locally while interpolating the shape of features determined in the previous step.
► A new shape matching based method to preserve the shape of features defined on apparel products, where the features can be easily specified on apparel products with very simple interactions. ► A new shape optimization method, which can be applied to discrete surfaces containing non-manifold entities and does not need to solve large linear systems.
This paper presents a novel feature based parameterization approach of human bodies from the unorganized cloud points and the parametric design method for generating new models based on the ...parameterization. The parameterization consists of two phases. First, the semantic feature extraction technique is applied to construct the feature wireframe of a human body from laser scanned 3D unorganized points. Secondly, the symmetric detail mesh surface of the human body is modeled. Gregory patches are utilized to generate G(super 1) continuous mesh surface interpolating the curves on feature wireframe. After that, a voxel-based algorithm adds details on the smooth G(super 1) continuous surface by the cloud points. Finally, the mesh surface is adjusted to become symmetric. Compared to other template fitting based approaches, the parameterization approach introduced in this paper is more efficient. The parametric design approach synthesizes parameterized sample models to a new human body according to user input sizing dimensions. It is based on a numerical optimization process. The strategy of choosing samples for synthesis is also introduced. Human bodies according to a wide range of dimensions can be generated by our approach. Different from the mathematical interpolation function based human body synthesis methods, the models generated in our method have the approximation errors minimized. All mannequins constructed by our approach have consistent feature patches, which benefits the design automation of customized clothes around human bodies a lot.
Manual plant phenotyping is slow, error prone, and labor intensive. In this letter, we present an automated robotic system for fast, precise, and noninvasive measurements using a new ...deep-learning-based next-best view planning pipeline. Specifically, we first use a deep neural network to estimate a set of candidate voxels for the next scanning. Next, we cast rays from these voxels to determine the optimal viewpoints. We empirically evaluate our method in simulations and real-world robotic experiments with up to three robotic arms to demonstrate its efficiency and effectiveness. One advantage of our new pipeline is that it can be easily extended to a multi-robot system where multiple robots move simultaneously according to the planned motions. Our system significantly outperforms the single robot in flexibility and planning time. High-throughput phenotyping can be made practically.
Data-driven methods for modeling the realistic shapeof 3D human bodies need to access datasets that contain a large amount of 3D human models. We develop a method based on sparse representation in ...this paper to represent 3D human models as signals of patches. Unlike the general mesh compression approaches, all mesh models used in a data-driven human modeling framework have the same mesh connectivity. By using this property, we segment a human model into patches containing the same number of vertices. L0-learning algorithm is selected to train an overcomplete dictionary matrix, which in turn introduces sparse representation of the dataset. Patch signals of individual human models can then be extracted by using the dictionary matrix. With the ease of balance control between sparsity and accuracy that is featured by the chosen learning algorithm, a representation with high compression ratio and low shape-approximation error can be determined. The results have been compared with the widely used statistic representation based on principal component analysis (PCA) to verify the effectiveness of our approach. Moreover, the method for using sparse representation in the regression-based statistical modeling of 3D human models has been presented at the end of the paper.
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•A sparse representation method for 3D human models with less memory consumption.•A method of constructing patch signals for generating a large amount of samples.•A controllable level of compression with higher accuracy in data-driven modeling.
Actuators using soft materials feature a large number of degrees of freedom. This tremendous flexibility allows a soft actuator to passively adapt its shape to the objects under interaction. In this ...paper, we propose a novel proprioception method for soft actuators during real-time interaction with previously unknown objects. First, we design a color-based sensing structure that instantly translates the inflation of a bellow into changes in color, which are subsequently detected by a miniaturized color sensor. The color sensor is small and, thus, multiple of them can be integrated into soft pneumatic actuators to reflect local deformations. Second, we make use of a feed-forward neural network to reconstruct a multivariate global shape deformation from local color signals. Our results demonstrate that deformations of the actuator during interaction, including sigmoid-like shapes, can be accurately reconstructed. The accurate shape sensing represents a significant step toward closed-loop control of soft robots in unstructured environments.
Uniform offsetting is an important geometric operation for computer-aided design and manufacturing (CAD/CAM) applications such as rapid prototyping, NC machining, coordinate measuring machines, robot ...collision avoidance, and
Hausdorff error calculation. We present a novel method for offsetting (grown and shrunk) a solid model by an arbitrary distance
r
. First, offset polygons are directly computed for each face, edge, and vertex of an input solid model. The computed polygonal meshes form a continuous boundary; however, such a boundary is invalid since there exist meshes that are closer to the original model than the given distance
r
as well as self-intersections. Based on the problematic polygonal meshes, we construct a well-structured point-based model,
Layered Depth-Normal Image (LDNI), in three orthogonal directions. The accuracy of the generated point-based model can be controlled by setting the tessellation and sampling rates during the construction process. We then process all the sampling points in the model by using a set of point filters to delete all the invalid points. Based on the remaining points, we construct a two-manifold polygonal contour as the resulting offset boundary. Our method is general, simple and efficient. We report experimental results on a variety of CAD models and discuss various applications of the developed uniform offsetting method.
► A general method to compute the uniform offsetting boundary of a two-manifold polygonal model and an arbitrary offset distance. ► Complex self-intersections in offset surfaces are trimmed based on a point-based method. ► Three point filters can efficiently remove non-boundary points. ► Two-manifold boundary surfaces are reconstructed from the unfiltered point.
Additive manufacturing (AM) is poised to bring about a revolution in the way products are designed, manufactured, and distributed to end users. This technology has gained significant academic as well ...as industry interest due to its ability to create complex geometries with customizable material properties. AM has also inspired the development of the maker movement by democratizing design and manufacturing. Due to the rapid proliferation of a wide variety of technologies associated with AM, there is a lack of a comprehensive set of design principles, manufacturing guidelines, and standardization of best practices. These challenges are compounded by the fact that advancements in multiple technologies (for example materials processing, topology optimization) generate a “positive feedback loop” effect in advancing AM. In order to advance research interest and investment in AM technologies, some fundamental questions and trends about the dependencies existing in these avenues need highlighting. The goal of our review paper is to organize this body of knowledge surrounding AM, and present current barriers, findings, and future trends significantly to the researchers. We also discuss fundamental attributes of AM processes, evolution of the AM industry, and the affordances enabled by the emergence of AM in a variety of areas such as geometry processing, material design, and education. We conclude our paper by pointing out future directions such as the “print-it-all” paradigm, that have the potential to re-imagine current research and spawn completely new avenues for exploration.
•The fundamental attributes and challenges/barriers of Additive Manufacturing (AM).•The evolution of research on AM with a focus on engineering capabilities.•The affordances enabled by AM such as geometry, material and tools design.•The developments in industry, intellectual property, and education-related aspects.•The important future trends of AM technologies.
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