3D Data Representation, Storage and Processing

Smith, William A. P.

doi:10.1007/978-3-030-44070-1_6

Cited by 1 publication

(6 citation statements)

References 78 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3D data representations serve as an intermediary between data Most geometric algorithms in computer vision and graphics operate on representations of 3D data based on surfaces. 31 Polygonal mesh, and more specifically triangular mesh, is by far the most common surface representation. It is a collection of vertices, edges, and faces that defines the shape of the object.…”

Section: Geometric Representationsmentioning

confidence: 99%

“…There is a wide range of systems for representing geometric 3D data. 3D data representations serve as an intermediary between data acquisition and application, with constraints imposed from both 31 . The various representations can be distinguished based on what is being represented, the amount of information available without derivation, and what information that can and cannot be derived.…”

Section: Analysis: Cascading Trade Studiesmentioning

confidence: 99%

“…3D representation can be categorized as raw data, surfaces, and solids 31 . Raw data are data that are delivered by a 3D sensor.…”

Section: Analysis: Cascading Trade Studiesmentioning

confidence: 99%

“…both the data acquisition method and the application impose constraints on the geometric representation, it might not be enough with one representation throughout the system. It can be necessary to convert between representations with some level of approximation 31. 3D representation can be categorized as raw data, surfaces, and solids 31.…”

mentioning

confidence: 99%

“…It can be necessary to convert between representations with some level of approximation 31. 3D representation can be categorized as raw data, surfaces, and solids 31. Raw data are data that are delivered by a 3D sensor.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Cascading trade‐off studies for robotic deburring systems

Onstein

Haskins

Semeniuta

2022

Systems Engineering

View full text Add to dashboard Cite

Advanced manufacturing technologies play an important role in keeping production in high‐cost countries. Due to their flexibility, robot‐based solutions have been one of the major enablers in establishing advanced manufacturing capabilities in the traditional high‐cost countries. This paper concerns the problem of automated deburring of cast parts. If performed manually, this operation introduces major health, safety, and environmental (HSE) concerns. As such, removal of highly variable casting burrs in the Norwegian context requires a solution based on robots, smart sensors, and advanced algorithms to tackle the problem in a flexible and cost‐effective way. Due to the complexity of the task, one is confronted with a breadth of various alternatives to choose from when realizing the desired functionality. These alternatives expand as one considers a pipeline of the subtasks involved in the process. The decisions made in each step cascade throughout the whole pipeline. To tackle the complexity while developing a robotized deburring system, a systemic approach based on cascading trade‐off studies is proposed in this paper. This paper is also a contribution to the gap in the literature for cases of trade‐off studies in the domain of mechanical engineering. The SPADE (stakeholders, problem formulation, analysis, decision making, and evaluation) methodology has been used as a framework to resolve automation of complex mechanical engineering manufacturing process decisions. The systems engineering (SE) approach proved useful to identify and prioritize the stakeholders and their needs, as well as analyzing the different alternatives in a complex engineering system when dealing with cascading trade studies.

show abstract

Section: Geometric Representationsmentioning

confidence: 99%

Section: Analysis: Cascading Trade Studiesmentioning

confidence: 99%

“…3D representation can be categorized as raw data, surfaces, and solids 31 . Raw data are data that are delivered by a 3D sensor.…”

Section: Analysis: Cascading Trade Studiesmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%