Automatic CAD Model Reconstruction from Multiple Point Clouds for Reverse Engineering

2002 ◽  
Vol 2 (3) ◽  
pp. 160-170 ◽  
Author(s):  
Jianbing Huang ◽  
Chia-Hsiang Menq
Keyword(s):  
Reverse Engineering ◽  
Boundary Surface ◽  
Point Clouds ◽  
Geometric Feature ◽  
Multiple Point ◽  
Reconstruction Method ◽  
Cad Model ◽  
Model Reconstruction ◽  
Triangle Mesh ◽  
Novel Technologies

In this paper, a systematic scheme is proposed and novel technologies are developed to automatically reconstruct a CAD model from a set of point clouds scanned from the boundary surface of an existing object. The proposed scheme is composed of three major steps. In the first step, multiple input point clouds are incrementally integrated into a watertight triangle mesh to recover the object shape. In the second step, mesh segmentation is applied to the triangle mesh to extract individual geometric feature surfaces. Finally, the manifold topology describing the connectivity information between different geometric surfaces is automatically extracted and the mathematical description of each geometric feature is computed. The computed topology and geometry information represented in ACIS modeling kernel form a CAD model that may be used for various downstream applications. Compared with prior work, the proposed approach has the unique advantage that the processes of recognizing geometric features and of reconstructing CAD models are fully automated. Integrated with state of the art scanning devices, the developed model reconstruction method can be used to support reverse engineering of high precision mechanical components. It has potential applications to many engineering problems with a major impact on rapid design and prototyping, shape analysis, and virtual reality.

A depth camera-based full-body reconstruction method for body pose training in occupational safety

2020 ◽  
Vol 64 (1) ◽  
pp. 1541-1545
Author(s):  
Li Li ◽  
Ken Chen ◽  
Karen Chen ◽  
Xu Xu*
Keyword(s):  
Occupational Injuries ◽  
Technological Development ◽  
Point Clouds ◽  
Incidence Rates ◽  
Multiple Point ◽  
Reconstruction Method ◽  
Safety Education ◽  
Depth Cameras ◽  
Work Related ◽  
Full Body

Occupational injuries have high incidence rates across various industries. Safety education is a key component to effectively reduce work-related injuries. Posture training for work safety is widely adopted to increase the awareness of unsafe movements at work and to evaluate workers to minimize work-related musculoskeletal stresses. However, existing one-size-fits-all pamphlet-based posture training is facing challenges in its effectiveness. In recent years, the substantial technological development in virtual reality (VR) and augmented reality (AR) has made immersive and personalized education possible. For VR/AR-assisted posture training, full-body reconstruction from multiple point clouds is the key step. In this study, we propose a fast and coarse method to reconstruct the full-body pose of safety instructors using multiple low-cost depth cameras. The reconstructed body images from depth cameras are registered through iterative closet point algorithm. The reconstructed full-body pose can be further rendered in VR/AR environments for next-generation safety education.

scholarly journals Algorithms for Precision

2016 ◽  
Vol 2 (3(4)) ◽  
pp. 16
Author(s):  
Dominik Schmid
Keyword(s):  
Reverse Engineering ◽  
Precise Measurement ◽  
Measurement Data ◽  
Point Clouds ◽  
Cad Model ◽  
Measuring Systems ◽  
Loss Of Information

ZEISS Reverse Engineering closes the gap between measuring systems and CAD programs. The software for reverse engineering and 3D point processing is particularly well-suited for users that want to convert into a CAD model their highly precise measurement data or the calculated point clouds without a loss of information.

3D CAD model reconstruction and fast prototyping of rotational parts: a reverse engineering approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Boppana V. Chowdary ◽  
Deepak Jaglal
Keyword(s):  
Reverse Engineering ◽  
Surface Model ◽  
Cad Model ◽  
Model Reconstruction ◽  
Cnc Machine ◽  
Content Type ◽  
3D Cad ◽  
Fast Prototyping ◽  
Computer Aided ◽  
Rotational Parts

Purpose This paper aims to present a reverse engineering (RE) approach for three-dimensional (3D) model reconstruction and fast prototyping (FP) of broken chess pieces. Design/methodology/approach A case study involving a broken chess piece was selected to demonstrate the effectiveness of the proposed unconventional RE approach. Initially, a laser 3D scanner was used to acquire a (non-uniform rational B-spline) surface model of the object, which was then processed to develop a parametric computer aided design (CAD) model combined with geometric design and tolerancing (GD&T) technique for evaluation and then for FP of the part using a computer numerical controlled (CNC) machine. Findings The effectiveness of the proposed approach for reconstruction and FP of rotational parts was ascertained through a sample part. The study demonstrates non-contact data acquisition technologies such as 3D laser scanners together with RE systems can support to capture the entire part geometry that was broken/worn and developed quickly through the application of computer aided manufacturing principles and a CNC machine. The results indicate that design communication, customer involvement and FP can be efficiently accomplished by means of an integrated RE workflow combined with rapid product development tools and techniques. Originality/value This research established a RE approach for the acquisition of broken/worn part data and the development of parametric CAD models. Then, the developed 3D CAD model was inspected for accuracy by means of the GD&T approach and rapidly developed using a CNC machine. Further, the proposed RE led FP approach can provide solutions to similar industrial situations wherein agility in the product design and development process is necessary to produce physical samples and functional replacement parts for aging systems in a short turnaround time.

Surface Reconstruction of Auto Outer Door Panel Based on Reverse Engineering

2011 ◽  
Vol 299-300 ◽  
pp. 1248-1251
Author(s):  
Guo Hong Tian ◽  
Xiu Chunb Wu ◽  
Xue Shenc Su ◽  
Kun Li
Keyword(s):  
Data Processing ◽  
Reverse Engineering ◽  
Surface Reconstruction ◽  
Point Clouds ◽  
Contour Line ◽  
Cad Model ◽  
Actual Object ◽  
Line Feature ◽  
Door Panel

The point clouds data of auto outer door panel is measured with CMM. After data processing and extracting of contour line feature, the surface is reconstructed in CATIA software. With the example, the process of reverse design how to acquire CAD model of product from actual object or sample is studied.

scholarly journals OICP: An Online Fast Registration Algorithm Based on Rigid Translation Applied to Wire Arc Additive Manufacturing of Mold Repair

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1563
Author(s):  
Ruibing Wu ◽  
Ziping Yu ◽  
Donghong Ding ◽  
Qinghua Lu ◽  
Zengxi Pan ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Point Cloud ◽  
Point Clouds ◽  
Iterative Closest Point ◽  
Multiple Point ◽  
Icp Algorithm ◽  
Registration Algorithm ◽  
Cloud Models ◽  
Comparison Results ◽  
Wire Arc Additive Manufacturing

As promising technology with low requirements and high depositing efficiency, Wire Arc Additive Manufacturing (WAAM) can significantly reduce the repair cost and improve the formation quality of molds. To further improve the accuracy of WAAM in repairing molds, the point cloud model that expresses the spatial distribution and surface characteristics of the mold is proposed. Since the mold has a large size, it is necessary to be scanned multiple times, resulting in multiple point cloud models. The point cloud registration, such as the Iterative Closest Point (ICP) algorithm, then plays the role of merging multiple point cloud models to reconstruct a complete data model. However, using the ICP algorithm to merge large point clouds with a low-overlap area is inefficient, time-consuming, and unsatisfactory. Therefore, this paper provides the improved Offset Iterative Closest Point (OICP) algorithm, which is an online fast registration algorithm suitable for intelligent WAAM mold repair technology. The practicality and reliability of the algorithm are illustrated by the comparison results with the standard ICP algorithm and the three-coordinate measuring instrument in the Experimental Setup Section. The results are that the OICP algorithm is feasible for registrations with low overlap rates. For an overlap rate lower than 60% in our experiments, the traditional ICP algorithm failed, while the Root Mean Square (RMS) error reached 0.1 mm, and the rotation error was within 0.5 degrees, indicating the improvement of the proposed OICP algorithm.

scholarly journals Canopy Parameter Estimation of Citrus grandis var. Longanyou Based on LiDAR 3D Point Clouds

2021 ◽  
Vol 13 (9) ◽  
pp. 1859
Author(s):  
Xiangyang Liu ◽  
Yaxiong Wang ◽  
Feng Kang ◽  
Yang Yue ◽  
Yongjun Zheng
Keyword(s):  
Convex Hull ◽  
Clustering Algorithm ◽  
Plant Protection ◽  
Point Clouds ◽  
Biomass Estimation ◽  
Reconstruction Method ◽  
Volume Calculation ◽  
Alpha Shape ◽  
3D Point Clouds ◽  
Canopy Volume

The characteristic parameters of Citrus grandis var. Longanyou canopies are important when measuring yield and spraying pesticides. However, the feasibility of the canopy reconstruction method based on point clouds has not been confirmed with these canopies. Therefore, LiDAR point cloud data for C. grandis var. Longanyou were obtained to facilitate the management of groves of this species. Then, a cloth simulation filter and European clustering algorithm were used to realize individual canopy extraction. After calculating canopy height and width, canopy reconstruction and volume calculation were realized using six approaches: by a manual method and using five algorithms based on point clouds (convex hull, CH; convex hull by slices; voxel-based, VB; alpha-shape, AS; alpha-shape by slices, ASBS). ASBS is an innovative algorithm that combines AS with slices optimization, and can best approximate the actual canopy shape. Moreover, the CH algorithm had the shortest run time, and the R2 values of VCH, VVB, VAS, and VASBS algorithms were above 0.87. The volume with the highest accuracy was obtained from the ASBS algorithm, and the CH algorithm had the shortest computation time. In addition, a theoretical but preliminarily system suitable for the calculation of the canopy volume of C. grandis var. Longanyou was developed, which provides a theoretical reference for the efficient and accurate realization of future functional modules such as accurate plant protection, orchard obstacle avoidance, and biomass estimation.

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