Volumetric view planning for 3D reconstruction with multiple manipulators

2015 ◽  
Vol 42 (6) ◽  
pp. 533-543 ◽  
Author(s):  
Liangzhi Li ◽  
Nanfeng Xiao
Keyword(s):  
Three Dimensional ◽  
Industrial Applications ◽  
Computationally Efficient ◽  
Object Reconstruction ◽  
View Planning ◽  
Reconstruction Process ◽  
Content Type ◽  
Speed Up ◽  
Next Best View ◽  
Multiple Manipulators

Purpose – This paper aims to propose a new view planning method which can be used to calculate the next-best-view (NBV) for multiple manipulators simultaneously and build an automated three-dimensional (3D) object reconstruction system, which is based on the proposed method and can adapt to various industrial applications. Design/methodology/approach – The entire 3D space is encoded with octree, which marks the voxels with different tags. A set of candidate viewpoints is generated, filtered and evaluated. The viewpoint with the highest score is selected as the NBV. Findings – The proposed method is able to make the multiple manipulators, equipped with “eye-in-hand” RGB-D sensors, work together to accelerate the object reconstruction process. Originality/value – Compared to the existed approaches, the proposed method in this paper is fast, computationally efficient, has low memory cost and can be used in actual industrial productions where the multiple different manipulators exist. And, more notably, a new algorithm is designed to speed up the generation and filtration of the candidate viewpoints, which can guarantee both speed and quality.

scholarly journals Multiscale, thermomechanical topology optimization of self-supporting cellular structures for porous injection molds

2019 ◽  
Vol 25 (9) ◽  
pp. 1482-1492
Author(s):  
Tong Wu ◽  
Andres Tovar
Keyword(s):  
Topology Optimization ◽  
Mechanical Performance ◽  
Mechanical Load ◽  
Design Method ◽  
Three Dimensional ◽  
Optimization Method ◽  
Cellular Structures ◽  
Injection Mold ◽  
Computationally Efficient ◽  
Content Type

Purpose This paper aims to establish a multiscale topology optimization method for the optimal design of non-periodic, self-supporting cellular structures subjected to thermo-mechanical loads. The result is a hierarchically complex design that is thermally efficient, mechanically stable and suitable for additive manufacturing (AM). Design/methodology/approach The proposed method seeks to maximize thermo-mechanical performance at the macroscale in a conceptual design while obtaining maximum shear modulus for each unit cell at the mesoscale. Then, the macroscale performance is re-estimated, and the mesoscale design is updated until the macroscale performance is satisfied. Findings A two-dimensional Messerschmitt Bolkow Bolhm (MBB) beam withstanding thermo-mechanical load is presented to illustrate the proposed design method. Furthermore, the method is implemented to optimize a three-dimensional injection mold, which is successfully prototyped using 420 stainless steel infiltrated with bronze. Originality/value By developing a computationally efficient and manufacturing friendly inverse homogenization approach, the novel multiscale design could generate porous molds which can save up to 30 per cent material compared to their solid counterpart without decreasing thermo-mechanical performance. Practical implications This study is a useful tool for the designer in molding industries to reduce the cost of the injection mold and take full advantage of AM.

scholarly journals A computationally-efficient secondary organic aerosol module for three-dimensional air quality models

2008 ◽  
Vol 8 (2) ◽  
pp. 7085-7110
Author(s):  
P. Liu ◽  
Y. Zhang
Keyword(s):  
Air Quality ◽  
Organic Compounds ◽  
Activity Coefficients ◽  
Three Dimensional ◽  
Computationally Efficient ◽  
Quality Models ◽  
Organic Mixtures ◽  
Speed Up ◽  
Numerical Solver ◽  
Aerosol Module

Abstract. Accurately simulating secondary organic aerosols (SOA) in three-dimensional (3-D) air quality models is challenging due to the complexity of the physics and chemistry involved and the high computational demand required. A computationally-efficient yet accurate SOA module is necessary in 3-D applications for long-term simulations and real-time air quality forecasting. A coupled gas and aerosol box model (i.e., 0-D CMAQ-MADRID 2) is used to optimize relevant processes in order to develop such a SOA module. Solving the partitioning equations for condensable volatile organic compounds (VOCs) and calculating their activity coefficients in the multicomponent mixtures are identified to be the most computationally-expensive processes. The two processes can be speeded up by relaxing the error tolerance levels and reducing the maximum number of iterations of the numerical solver for the partitioning equations for organic species; turning on organic-inorganic interactions only when the water content associated with organic compounds is significant; and parameterizing the calculation of activity coefficients for organic mixtures in the hydrophilic module. The optimal speed-up method can reduce the total CPU cost by up to a factor of 29.7 with ±15% deviation from benchmark results. These speedup methods are applicable to other SOA modules that are based on partitioning theories.

Design of fluid components using the topological optimization method

2019 ◽  
Vol 36 (5) ◽  
pp. 1430-1448
Author(s):  
L.C. Ruspini ◽  
E. Dari ◽  
C. Padra ◽  
G.H. Paissan ◽  
N.N. Salva
Keyword(s):  
Stokes Equations ◽  
Fluid Dynamic ◽  
Three Dimensional ◽  
Optimization Method ◽  
Industrial Applications ◽  
Design Tool ◽  
Three Dimensions ◽  
Topological Optimization ◽  
Engineering Structures ◽  
Content Type

Purpose The purpose of this paper is to present applications of the topological optimization method dealing with fluid dynamic problems in two- and three dimensions. The main goal is to develop a tool package able to optimize topology in realistic devices (e.g. inlet manifolds) considering the non-linear terms on Navier–Stokes equations. Design/methodology/approach Using an in-house Fortran code, a Galerkin stabilized finite element is implemented method to solve the three equation systems necessary for the topological optimization method: the direct problem, adjoint problem and topological derivative. The authors address the non-linearity in the equations using an iterative method. Different techniques to create holes into a two-dimensional discrete domain are analyzed. Findings One technique to create holes produces more accurate and robust results. The authors present several examples of applications in two- and three-dimensional components, which highlight the potential of this method in the optimization of fluid components. Research limitations/implications The authors contribute to the methodology and design in engineering. Practical implications Engineering fluid flow systems are used in many different industrial applications, e.g. oil flow in pipes; air flow around an airplane wing; sailing submarines; blood flow in synthetic arteries; and thermal and fissure spreading problems. The aim of this work is to create an effective design tool for obtaining efficient engineering structures and devices. Originality/value The authors contribute by creating an application of the method to design a tridimensional realistic device, which can be essayed experimentally. Particularly, the authors apply the design tool to an inlet manifold.

scholarly journals A computationally-efficient secondary organic aerosol module for three-dimensional air quality models

2008 ◽  
Vol 8 (14) ◽  
pp. 3985-3998 ◽  
Author(s):  
P. Liu ◽  
Y. Zhang
Keyword(s):  
Air Quality ◽  
Activity Coefficients ◽  
Three Dimensional ◽  
Computationally Efficient ◽  
Quality Models ◽  
Organic Mixtures ◽  
Speed Up ◽  
Numerical Solver ◽  
Aerosol Module

Abstract. Accurately simulating secondary organic aerosols (SOA) in three-dimensional (3-D) air quality models is challenging due to the complexity of the physics and chemistry involved and the high computational demand required. A computationally-efficient yet accurate SOA module is necessary in 3-D applications for long-term simulations and real-time air quality forecasting. A coupled gas and aerosol box model (i.e., 0-D CMAQ-MADRID 2) is used to optimize relevant processes in order to develop such a SOA module. Solving the partitioning equations for condensable volatile organic compounds (VOCs) and calculating their activity coefficients in the multicomponent mixtures are identified to be the most computationally-expensive processes. The two processes can be speeded up by relaxing the error tolerance levels and reducing the maximum number of iterations of the numerical solver for the partitioning equations for organic species; conditionally activating organic-inorganic interactions; and parameterizing the calculation of activity coefficients for organic mixtures in the hydrophilic module. The optimal speed-up method can reduce the total CPU cost by up to a factor of 31.4 from benchmark under the rural conditions with 2 ppb isoprene and by factors of 10–71 under various test conditions with 2–10 ppb isoprene and >40% relative humidity while maintaining ±15% deviation. These speed-up methods are applicable to other SOA modules that are based on partitioning theories.

View planning for automated three-dimensional object reconstruction and inspection

2003 ◽  
Vol 35 (1) ◽  
pp. 64-96 ◽  
Author(s):  
William R. Scott ◽  
Gerhard Roth ◽  
Jean-François Rivest
Keyword(s):  
Three Dimensional ◽  
Object Reconstruction ◽  
View Planning ◽  
Dimensional Object

scholarly journals Volumetric Next-best-view Planning for 3D Object Reconstruction with Positioning Error

10.5772/58759 ◽  
2014 ◽  
Vol 11 (10) ◽  
pp. 159 ◽  
Author(s):  
J. Irving Vasquez-Gomez ◽  
L. Enrique Sucar ◽  
Rafael Murrieta-Cid ◽  
Efrain Lopez-Damian
Keyword(s):  
Positioning Error ◽  
Object Reconstruction ◽  
View Planning ◽  
3D Object ◽  
3D Object Reconstruction ◽  
Next Best View

scholarly journals An active reconstruction algorithm based on partial prior information

2020 ◽  
Vol 17 (1) ◽  
pp. 172988142090420
Author(s):  
Yanzi Kong ◽  
Feng Zhu ◽  
Yingming Hao ◽  
Haibo Sun ◽  
Yilin Xie ◽  
...  
Keyword(s):  
Prior Information ◽  
Active Vision ◽  
Reconstruction Algorithm ◽  
Shape Estimation ◽  
Object Reconstruction ◽  
View Planning ◽  
Visual Tasks ◽  
Motion Paths ◽  
Active Reconstruction ◽  
Next Best View

Active reconstruction is an intelligent perception method that achieves object modeling with few views and short motion paths by systematically adjusting the parameters of the camera while ensuring model integrity. Part of the object information is always known for vision tasks in real scenes, and it provides some guidance for the view planning. A two-step active reconstruction algorithm based on partial prior information is presented, which includes rough shape estimation phase and complete object reconstruction phase, and both of them introduce the concept of active vision. An information expression method is proposed that can be used to manually initialize the repository according to specific visual tasks, and then the prior information and detected information are used to plan the next best view online until the object reconstruction is completed. The method is evaluated with simulated experiments and the result is compared with other methods.

Construction of poly-ellipsoidal grain shapes from SMT imaging on sand, and the development of a new DEM contact detection algorithm

2018 ◽  
Vol 35 (2) ◽  
pp. 733-771 ◽  
Author(s):  
Boning Zhang ◽  
Richard Regueiro ◽  
Andrew Druckrey ◽  
Khalid Alshibli
Keyword(s):  
Particle Shape ◽  
Detection Algorithm ◽  
Contact Detection ◽  
Computationally Efficient ◽  
Content Type ◽  
Contact Algorithm ◽  
Shape Approximation ◽  
Speed Up ◽  
Contact Detection Algorithm ◽  
Particle Shapes

Purpose This paper aims to construct smooth poly-ellipsoid shapes from synchrotron microcomputed tomography (SMT) images on sand and to develop a new discrete element method (DEM) contact detection algorithm. Design/methodology/approach Voxelated images generated by SMT on Colorado Mason sand are processed to construct smooth poly-ellipsoidal particle approximations. For DEM contact detection, cuboidal shape approximations to the poly-ellipsoids are used to speed up contact detection. Findings The poly-ellipsoid particle shape approximation to Colorado Mason sand grains is better than a simpler ellipsoidal approximation. The new DEM contact algorithm leads to significant speedup and accuracy is maintained. Research limitations/implications The paper limits particle shape approximation to smooth poly-ellipsoids. Practical implications Poly-ellipsoids provide asymmetry of particle shapes as compared to ellipsoids, thus allowing closer representation of real sand grain shapes that may be angular and unsymmetric. When incorporated in a DEM for computation, the poly-ellipsoids allow better representation of particle rolling, sliding and interlocking phenomena. Originality/value Method to construct poly-ellipsoid particle shapes from SMT data on real sands and computationally efficient DEM contact detection algorithm for poly-ellipsoids.

Accelerating unstructured large eddy simulation solver with GPU

2018 ◽  
Vol 35 (5) ◽  
pp. 2025-2049 ◽  
Author(s):  
Hongbin Liu ◽  
Xinrong Su ◽  
Xin Yuan
Keyword(s):  
Large Eddy Simulation ◽  
Finite Volume ◽  
Three Dimensional ◽  
Finite Volume Scheme ◽  
High Fidelity ◽  
Double Precision ◽  
Content Type ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Speed Up

Purpose Adopting large eddy simulation (LES) to simulate the complex flow in turbomachinery is appropriate to overcome the limitation of current Reynolds-Averaged Navier–Stokes modelling and it provides a deeper understanding of the complicated transitional and turbulent flow mechanism; however, the large computational cost limits its application in high Reynolds number flow. This study aims to develop a three-dimensional GPU-enabled parallel-unstructured solver to speed up the high-fidelity LES simulation. Design/methodology/approach Compared to the central processing units (CPUs), graphics processing units (GPUs) can provide higher computational speed. This work aims to develop a three-dimensional GPU-enabled parallel-unstructured solver to speed up the high-fidelity LES simulation. A set of low-dissipation schemes designed for unstructured mesh is implemented with compute unified device architecture programming model. Several key parameters affecting the performance of the GPU code are discussed and further speed-up can be obtained by analysing the underlying finite volume-based numerical scheme. Findings The results show that an acceleration ratio of approximately 84 (on a single GPU) for double precision algorithm can be achieved with this unstructured GPU code. The transitional flow inside a compressor is simulated and the computational efficiency has been improved greatly. The transition process is discussed and the role of K-H instability playing in the transition mechanism is verified. Practical/implications The speed-up gained from GPU-enabled solver reaches 84 compared to original code running on CPU and the vast speed-up enables the fast-turnaround high-fidelity LES simulation. Originality/value The GPU-enabled flow solver is implemented and optimized according to the feature of finite volume scheme. The solving time is reduced remarkably and the detail structures including vortices are captured.

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