scholarly journals Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

2021 ◽  
Author(s):  
Carmelo Mineo ◽  
Donatella Cerniglia ◽  
Vito Ricotta ◽  
Bernhard Reitinger
Keyword(s):  
Optical Sensors ◽  
Point Cloud ◽  
Simulation Software ◽  
Surface Mapping ◽  
Part Geometry ◽  
Industrial Sectors ◽  
3D Geometry ◽  
Part Surface ◽  
Lot Sizes ◽  
Specific Part

AbstractMany industrial sectors face increasing production demands and the need to reduce costs, without compromising the quality. The use of robotics and automation has grown significantly in recent years, but versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are excessive differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. Previous works have demonstrated the use of robot-manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized for a specific part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The novelty of this work lies in enabling the capability of mapping a part surface at the required level of sampling density, whilst minimizing the number of necessary view poses. Its development has also led to an efficient method of point cloud down-sampling and merging. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences.

scholarly journals Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

2021 ◽  
Author(s):  
Carmelo Mineo ◽  
Donatella Cerniglia ◽  
Vito Ricotta ◽  
Bernhard Reitinger
Keyword(s):  
Optical Sensors ◽  
Simulation Software ◽  
Surface Mapping ◽  
Part Geometry ◽  
Industrial Sectors ◽  
3D Geometry ◽  
Real Geometry ◽  
Lot Sizes ◽  
Small Production ◽  
Robot Task

Abstract Many industrial sectors face increasing production demands and need to reduce costs, without compromising the quality. Whereas mass production relies on well-established protocols, small production facilities with small lot sizes struggle to update their highly changeable production at reasonable costs. The use of robotics and automation has grown significantly in recent years, but extremely versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are unavoidable differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. This could be avoided by measuring the real-geometry and the position of the specimen, which creates the paradox of having to plan robot paths for surface mapping purposes, before the originally intended robot task can be approached. Previous works have demonstrated the use of robotically manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized to the part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences.

A Preliminary Experimental Study of Additive Manufacturing Energy Consumption

2017 ◽  
Author(s):  
Daniel Dunaway ◽  
James Dillon Harstvedt ◽  
Junfeng Ma
Keyword(s):  
Energy Consumption ◽  
Additive Manufacturing ◽  
Experimental Design ◽  
Surface Area ◽  
Surface Geometry ◽  
Fused Deposition ◽  
Part Geometry ◽  
Industrial Sectors ◽  
Part Surface ◽  
The Impact

Additive manufacturing (AM) refers to a group of manufacturing techniques that produce components by melting and bonding material powders in a layer-by-layer fashion. By virtue of its capability of producing parts with complex geometry and functionally graded materials, AM is leading the charge of the “third industrial revolution” and has attracted great attention in multiple industrial sectors, such as manufacturing, healthcare, aerospace, and others. Sustainability of AM remains an open question. AM is inherently an energy expensive process and may be energy inefficient as compared to the traditional manufacturing process. Thus, there exists an urgent need to identify the key influence factors and quantify the energy consumption during AM production. The proposed study aims to obtain a preliminary understanding of the impact of part surface geometry on AM energy consumption. The study addresses the effect of part geometry on AM energy consumption through experimental design method. Part geometry consists of two level meanings, part surface area and part surface complexity. The study utilizes a MakerGear M2 fused deposition modeling (FDM) 3D printer to complete the designed experiments. By implementing experimental design and statistical analysis technologies, the study firstly identifies the correlation between part geometry and AM energy consumption. The result shows that part surface area is positively correlated with AM energy consumption and no significant statistical evidence to support that part surface complexity is associated with AM energy consumption. Such findings are of significance to AM energy consumption in terms of both qualitative and quantitative analysis. In addition, the study has significant potentials to guide the future AM energy consumption model development and to be extended to future AM process improvement.

scholarly journals Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 201
Author(s):  
Michael Bekele Maru ◽  
Donghwan Lee ◽  
Kassahun Demissie Tola ◽  
Seunghee Park
Keyword(s):  
Optical Sensors ◽  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Depth Camera ◽  
Terrestrial Laser Scanner ◽  
Cloud Data ◽  
3D Point Clouds ◽  
3D Information

Modeling a structure in the virtual world using three-dimensional (3D) information enhances our understanding, while also aiding in the visualization, of how a structure reacts to any disturbance. Generally, 3D point clouds are used for determining structural behavioral changes. Light detection and ranging (LiDAR) is one of the crucial ways by which a 3D point cloud dataset can be generated. Additionally, 3D cameras are commonly used to develop a point cloud containing many points on the external surface of an object around it. The main objective of this study was to compare the performance of optical sensors, namely a depth camera (DC) and terrestrial laser scanner (TLS) in estimating structural deflection. We also utilized bilateral filtering techniques, which are commonly used in image processing, on the point cloud data for enhancing their accuracy and increasing the application prospects of these sensors in structure health monitoring. The results from these sensors were validated by comparing them with the outputs from a linear variable differential transformer sensor, which was mounted on the beam during an indoor experiment. The results showed that the datasets obtained from both the sensors were acceptable for nominal deflections of 3 mm and above because the error range was less than ±10%. However, the result obtained from the TLS were better than those obtained from the DC.

Wrinkling Prediction and Optimization of Sheet Metal Forming Process by Numerical Simulation

2015 ◽  
Vol 818 ◽  
pp. 252-255 ◽  
Author(s):  
Ján Slota ◽  
Marek Šiser
Keyword(s):  
Numerical Simulation ◽  
Material Model ◽  
Mechanical Tests ◽  
Simulation Software ◽  
Forming Process ◽  
Part Geometry ◽  
Nominal Thickness ◽  
430 Stainless Steel ◽  
Metal Forming Process ◽  
Aisi 430

The paper deals with optimization of forming process for AISI 430 stainless steel with nominal thickness 0.4 mm. During forming of sidewall for washing machine drum, some wrinkles remain at the end of forming process in some places. This problem was solved by optimization the geometry of the drawpiece using numerical simulation. During optimization a series of modifications of the part geometry to absolute elimination of wrinkling was performed. On the basis of mechanical tests, the material model was created and imported into the material database of Autoform simulation software.

scholarly journals Underwater-Sonar-Image-Based 3D Point Cloud Reconstruction for High Data Utilization and Object Classification Using a Neural Network

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1763
Author(s):  
Minsung Sung ◽  
Jason Kim ◽  
Hyeonwoo Cho ◽  
Meungsuk Lee ◽  
Son-Cheol Yu
Keyword(s):  
Neural Network ◽  
Point Cloud ◽  
Field Experiments ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Object Classification ◽  
High Data ◽  
3D Geometry ◽  
Underwater Object ◽  
3D Point Cloud Reconstruction

This paper proposes a sonar-based underwater object classification method for autonomous underwater vehicles (AUVs) by reconstructing an object’s three-dimensional (3D) geometry. The point cloud of underwater objects can be generated from sonar images captured while the AUV passes over the object. Then, a neural network can predict the class given the generated point cloud. By reconstructing the 3D shape of the object, the proposed method can classify the object accurately through a straightforward training process. We verified the proposed method by performing simulations and field experiments.

Error Minimization in Layered Manufacturing Parts by Stereolithography File Modification Using a Vertex Translation Algorithm

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Gaurav Navangul ◽  
Ratnadeep Paul ◽  
Sam Anand
Keyword(s):  
Layered Manufacturing ◽  
Conversion Error ◽  
File Size ◽  
Profile Error ◽  
Multiple Points ◽  
New Approach ◽  
Stl File ◽  
Part Geometry ◽  
Translation Error ◽  
Part Surface

Layered manufacturing (LM) machines use stereolithography (STL) files to build parts by creating continuous slices on top of each other. An STL file approximates the surface of a part with planar triangles. This results in geometric errors being introduced in the part surface during the conversion from the CAD model to the STL file format, which in turn leads to errors in the LM manufactured part. CAD packages have built-in export options to reduce this CAD to STL conversion error. However, this is applied to the entire part geometry which leads to an increase in the file size and preprocessing time in LM machines. This paper presents a new approach to locally reduce this CAD to STL translation error. This approach, referred to as vertex translation algorithm (VTA), compares an STL facet to its corresponding CAD surface, computes the chordal error at multiple points on the STL surface, and translates the point with the maximum chordal error until it lies on the design surface. This translation results in the reduction of the chordal error locally without unnecessarily increasing the size of the STL file. In addition, a facet isolation algorithm (FIA) has also been developed and presented in this paper. This isolation algorithm extracts the STL facets corresponding to the surfaces and features of the part that have to be modified by the translation algorithm. The VTA is applied in conjunction with the FIA on a sample service part to reduce the form and profile error of critical features of the part in order to satisfy the tolerance callouts on the part.

Optimal Tool Orientation for Five-Axis Tool-End Machining by Swept Envelope Approach

2004 ◽  
Author(s):  
John C. J. Chiou ◽  
Yuan-Shin Lee
Keyword(s):  
Tool Path ◽  
Tool Orientation ◽  
Error Sources ◽  
Part Geometry ◽  
Machining Errors ◽  
Nc Simulation ◽  
Part Surface ◽  
Tool Motion ◽  
Five Axis ◽  
Cutting Direction

This paper presents a swept envelope approach to determining the optimal tool orientation for five-axis tool-end machining. The swept profile of the cutter is determined based on the tool motion. By analyzing the swept profile against the part geometry, four types of machining errors (local gouge, side gouge, rear gouge, and global collision) are identified. The tool orientation is then corrected to avoid such errors. The cutter’s swept envelope is further constructed by integrating the intermediate swept profiles, and can be applied to NC simulation and verification. This paper presents the explicit solution for the swept profile of a general cutter in five-axis tool-end machining. The relation of the swept profile, the part geometry, the tool motion, and the machining errors is developed. Therefore, the error sources can be detected early and prevented during tool path planning. The analytical results indicate that the optimal tool orientation occurs when the curvature of the cutter’s swept profile matches with the curvature of the local part surface. In addition, the optimal cutting direction generally follows the minimum curvature direction. Computer illustrations and example demonstrations are shown in this paper. The results reveal the developed method can accurately determine the optimal tool orientation and efficiently avoid machining errors for five-axis tool-end machining.

scholarly journals Optimisation of Mould Design for Injection Moulding – Numerical Approach

2021 ◽  
Vol 15 (2) ◽  
pp. 258-266
Author(s):  
Damir Godec ◽  
Vladimir Brnadić ◽  
Tomislav Breški
Keyword(s):  
Computer Simulation ◽  
Injection Moulding ◽  
Numerical Approach ◽  
Processing Parameters ◽  
Simulation Software ◽  
Moulding Process ◽  
Part Geometry ◽  
Injection Moulding Process ◽  
Mould Cavity ◽  
Mould Design

Computer simulation of injection moulding process is a powerful tool for optimisation of moulded part geometry, mould design and processing parameters. One of the most frequent faults of the injection moulded parts is their warpage, which is a result of uneven cooling conditions in the mould cavity as well as after part ejection from the mould and cooling down to the environmental temperature. With computer simulation of the injection moulding process it is possible to predict potential areas of moulded part warpage and to apply the remedies to compensate/minimize the value of the moulded part warpage. The paper presents application of simulation software Moldex 3D in the process of optimising mould design for injection moulding of thermoplastic casing.

scholarly journals LADM AND INDOORGML FOR SUPPORT OF INDOOR SPACE IDENTIFICATION

2016 ◽  
Vol IV-2/W1 ◽  
pp. 257-263 ◽  
Author(s):  
S. Zlatanova ◽  
P. J. M. Van Oosterom ◽  
J. Lee ◽  
K.-J. Li ◽  
C. H. J. Lemmen
Keyword(s):  
Indoor Environment ◽  
Domain Model ◽  
Shopping Malls ◽  
Indoor Space ◽  
Space Subdivision ◽  
Land Administration ◽  
3D Geometry ◽  
The Status ◽  
Building Components ◽  
Specific Part

Guidance and security in large public buildings such as airports, museums and shopping malls requires much more information that traditional 2D methods offer. Therefore 3D semantically-reach models have been actively investigated with the aim to gather knowledge about availability and accessibility of spaces. Spaces can be unavailable to specific users because of plenty of reasons: the 3D geometry of spaces (too low, too narrow), the properties of the objects to be guided to a specific part of the building (walking, driving, flying), the status of the indoor environment (e.g. crowded, limited light, under reconstruction), property regulations (private areas), security considerations and so on. <br><br> However, such information is not explicitly avaible in the existing 3D semantically-reach models. IFC and CityGML are restricted to architectural building components and provide little to no means to describe such properties. IndoorGML has been designed to establish a generic approach for space identification allowing a space subdivision and automatic creation of a network for route computation. But currently it also represents only spaces as they are defined by the architectural layout of the building. The Land Administration Domain Model is currently the only available model to specify spaces on the basis of ownership and rights for use. <br><br> In this paper we compare the principles of IndoorGML and LADM, investigate the approaches to define spaces and suggest options to the linking of the two types of spaces. We argue that LADM space subdivision on basis of properties and rights of use can be used to define to semantically and geometrically available and accessible spaces and therefore can enrich the IndoorGML concept.

Research and Practice on New Measuring and Drafting Mode of Mechanical Drawing Based on Reverse Engineering

2012 ◽  
Vol 239-240 ◽  
pp. 645-648 ◽  
Author(s):  
Dong Yang Fang ◽  
Ai Mei Zhang ◽  
Yi Qiu
Keyword(s):  
Reverse Engineering ◽  
Point Cloud ◽  
Teaching Practice ◽  
Geometric Model ◽  
Three Dimensional ◽  
Surface Shape ◽  
Modern Engineering ◽  
Innovative Idea ◽  
Part Surface ◽  
Graphics Processing

New mode of measurement and draft in mechanical drawing based on reverse engineering is presented to reflect the idea of modern engineering design on teaching practice. Traditional measurement tools are replaced by three-dimensional scanner, whereas graphics processing is performed by using CAD technology. The processing includes three steps. Firstly, point cloud of part surface shape is obtained through scanning. Secondly, point cloud images are joined, filtered and latticed in Geomagic, which is application software of CAD. Finally, the processed point cloud is imported into Catia to reconstruct surface and three-dimensional geometric model. An innovative method of measurement and draft is accordingly proposed, which combines teaching and practices and helps to cultivate the innovative idea and abilities of students.

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