105 research outputs found

    Geometric reasoning for process planning

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    Evaluating the boundary and covering degree of planar Minkowski sums and other geometrical convolutions

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    AbstractAlgorithms are developed, based on topological principles, to evaluate the boundary and โ€œinternal structureโ€ of the Minkowski sum of two planar curves. A graph isotopic to the envelope curve is constructed by computing its characteristic points. The edges of this graph are in one-to-one correspondence with a set of monotone envelope segments. A simple formula allows a degree to be assigned to each face defined by the graph, indicating the number of times its points are covered by the Minkowski sum. The boundary can then be identified with the set of edges that separate faces of zero and non-zero degree, and the boundary segments corresponding to these edges can be approximated to any desired geometrical accuracy. For applications that require only the Minkowski sum boundary, the algorithm minimizes geometrical computations on the โ€œinternalโ€ envelope edges, that do not contribute to the final boundary. In other applications, this internal structure is of interest, and the algorithm provides comprehensive information on the covering degree for different regions within the Minkowski sum. Extensions of the algorithm to the computation of Minkowski sums in R3, and other forms of geometrical convolution, are briefly discussed

    Optimisation of surface coverage paths used by a non-contact robot painting system

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    This thesis proposes an efficient path planning technique for a non-contact optical โ€œpaintingโ€ system that produces surface images by moving a robot mounted laser across objects covered in photographic emulsion. In comparison to traditional 3D planning approaches (e.g. laminar slicing) the proposed algorithm dramatically reduces the overall path length by optimizing (i.e. minimizing) the amounts of movement between robot configurations required to position and orientate the laser. To do this the pixels of the image (i.e. points on the surface of the object) are sequenced using configuration space rather than Cartesian space. This technique extracts data from a CAD model and then calculates the configuration that the five degrees of freedom system needs to assume to expose individual pixels on the surface. The system then uses a closest point analysis on all the major joints to sequence the points and create an efficient path plan for the component. The implementation and testing of the algorithm demonstrates that sequencing points using a configuration based method tends to produce significantly shorter paths than other approaches to the sequencing problem. The path planner was tested with components ranging from simple to complex and the paths generated demonstrated both the versatility and feasibility of the approach

    Automatic tool path generation for multi-axis machining

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    Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1998.Includes bibliographical references (leaves 67-72).We present a novel approach to CAD/CAM integration for multi-axis machining. Instead of redefining the workpiece in terms of machining features, we generate tool paths directly by analyzing the accessibility of the surface of the part. This eliminates the problem of feature extraction. We envision this as the core strategy of a new direct and seamless CAD/ CAM system. We perform the accessibility analysis in two stages. First, we triangulate the surface of the workpiece and perform a visibility analysis from a discrete set of orientations arranged on the Gaussian Sphere. This analysis is performed in object space to ensure reliability. For each triangle, a discrete set approximation of the accessibility cone is then constructed. Next, a minimum set cover algorithm like the Quine-McCluskey Algorithm is used to select the minimum set of orientations from which the entire workpiece can be accessed. These set of orientations correspond to the setups in the machining plan, and also dictate the orientation in which the designed part will be embedded in the stock. In particular, we bias the search for setups in favor of directions from which most of the part can be accessed i.e, the parallel and perpendicular directions of the faces in the workpiece. For each setup, we select a set of tools for optimal removal of material. Our tool-path generation strategy is based on two general steps: global roughing and facebased finishing. In global roughing, we represent the workpiece and stock in a voxelized format. We perform a waterline analysis and slice the stock into material removal slabs. In each slab, we generate zig-zag tool paths for removing bulk of the material. After gross material removal in global roughing, we finish the faces of the component in face-based finishing. Here, instead of assembling faces into features, we generate tool paths directly and independently for each face. The accessibility cones are used to help ensure interference- free cuts. After the tool paths have been generated, we optimize the plan to ensure that commonalities between adjacent faces are exploited.by Laxmiprasad Putta.S.M

    ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ฒ€์ถœ ๋ฐ ์ œ๊ฑฐ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€,2020. 2. ๊น€๋ช…์ˆ˜.Offset curves and surfaces have many applications in computer-aided design and manufacturing, but the self-intersections and redundancies must be trimmed away for their practical use. We present a new method for offset curve and surface trimming that detects the self-intersections and eliminates the redundant parts of an offset curve and surface that are closer than the offset distance to the original curve and surface. We first propose an offset trimming method based on constructing geometric constraint equations. We formulate the constraint equations of the self-intersections of an offset curve and surface in the parameter domain of the original curve and surface. Numerical computations based on the regularity and intrinsic properties of the given input curve and surface is carried out to compute the solution of the constraint equations. The method deals with numerical instability around near-singular regions of an offset surface by using osculating tori that can be constructed in a highly stable way, i.e., by offsetting the osculating torii of the given input regular surface. We reveal the branching structure and the terminal points from the complete self-intersection curves of the offset surface. From the observation that the trimming method based on the multivariate equation solving is computationally expensive, we also propose an acceleration technique to trim an offset curve and surface. The alternative method constructs a bounding volume hierarchy specially designed to enclose the offset curve and surface and detects the self-collision of the bounding volumes instead. In the case of an offset surface, the thickness of the bounding volumes is indirectly determined based on the maximum deviations of the positions and the normals between the given input surface patches and their osculating tori. For further acceleration, the bounding volumes are pruned as much as possible during self-collision detection using various geometric constraints imposed on the offset surface. We demonstrate the effectiveness of the new trimming method using several non-trivial test examples of offset trimming. Lastly, we investigate the problem of computing the Voronoi diagram of a freeform surface using the offset trimming technique for surfaces. By trimming the offset surface with a gradually changing offset radius, we compute the boundary of the Voronoi cells that appear in the concave side of the given input surface. In particular, we interpret the singular and branching points of the self-intersection curves of the trimmed offset surfaces in terms of the boundary elements of the Voronoi diagram.์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์€ computer-aided design (CAD)์™€ computer-aided manufacturing (CAM)์—์„œ ๋„๋ฆฌ ์ด์šฉ๋˜๋Š” ์—ฐ์‚ฐ๋“ค ์ค‘ ํ•˜๋‚˜์ด๋‹ค. ํ•˜์ง€๋งŒ ์‹ค์šฉ์ ์ธ ํ™œ์šฉ์„ ์œ„ํ•ด์„œ๋Š” ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์—์„œ ์ƒ๊ธฐ๋Š” ์ž๊ฐ€ ๊ต์ฐจ๋ฅผ ์ฐพ๊ณ  ์ด๋ฅผ ๊ธฐ์ค€์œผ๋กœ ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์—์„œ ์›๋ž˜์˜ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์— ๊ฐ€๊นŒ์šด ๋ถˆํ•„์š”ํ•œ ์˜์—ญ์„ ์ œ๊ฑฐํ•˜์—ฌ์•ผํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์—์„œ ์ƒ๊ธฐ๋Š” ์ž๊ฐ€ ๊ต์ฐจ๋ฅผ ๊ณ„์‚ฐํ•˜๊ณ , ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์—์„œ ์ƒ๊ธฐ๋Š” ๋ถˆํ•„์š”ํ•œ ์˜์—ญ์„ ์ œ๊ฑฐํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์šฐ์„  ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ์ ๋“ค๊ณผ ๊ทธ ๊ต์ฐจ์ ๋“ค์ด ๊ธฐ์ธํ•œ ์›๋ž˜ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ ๋“ค์ด ์ด๋ฃจ๋Š” ํ‰๋ฉด ์ด๋“ฑ๋ณ€ ์‚ผ๊ฐํ˜• ๊ด€๊ณ„๋กœ๋ถ€ํ„ฐ ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ์ ์˜ ์ œ์•ฝ ์กฐ๊ฑด์„ ๋งŒ์กฑ์‹œํ‚ค๋Š” ๋ฐฉ์ •์‹๋“ค์„ ์„ธ์šด๋‹ค. ์ด ์ œ์•ฝ์‹๋“ค์€ ์›๋ž˜ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ๋ณ€์ˆ˜ ๊ณต๊ฐ„์—์„œ ํ‘œํ˜„๋˜๋ฉฐ, ์ด ๋ฐฉ์ •์‹๋“ค์˜ ํ•ด๋Š” ๋‹ค๋ณ€์ˆ˜ ๋ฐฉ์ •์‹์˜ ํ•ด๋ฅผ ๊ตฌํ•˜๋Š” solver๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ตฌํ•œ๋‹ค. ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ๊ฒฝ์šฐ, ์›๋ž˜ ๊ณก๋ฉด์˜ ์ฃผ๊ณก๋ฅ  ์ค‘ ํ•˜๋‚˜๊ฐ€ ์˜คํ”„์…‹ ๋ฐ˜์ง€๋ฆ„์˜ ์—ญ์ˆ˜์™€ ๊ฐ™์„ ๋•Œ ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ๋ฒ•์„ ์ด ์ •์˜๊ฐ€ ๋˜์ง€ ์•Š๋Š” ํŠน์ด์ ์ด ์ƒ๊ธฐ๋Š”๋ฐ, ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์ด ์ด ๋ถ€๊ทผ์„ ์ง€๋‚  ๋•Œ๋Š” ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์˜ ๊ณ„์‚ฐ์ด ๋ถˆ์•ˆ์ •ํ•ด์ง„๋‹ค. ๋”ฐ๋ผ์„œ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์ด ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ํŠน์ด์  ๋ถ€๊ทผ์„ ์ง€๋‚  ๋•Œ๋Š” ์˜คํ”„์…‹ ๊ณก๋ฉด์„ ์ ‘์ด‰ ํ† ๋Ÿฌ์Šค๋กœ ์น˜ํ™˜ํ•˜์—ฌ ๋” ์•ˆ์ •๋œ ๋ฐฉ๋ฒ•์œผ๋กœ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์„ ๊ตฌํ•œ๋‹ค. ๊ณ„์‚ฐ๋œ ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์œผ๋กœ๋ถ€ํ„ฐ ๊ต์ฐจ ๊ณก์„ ์˜ xyzxyz-๊ณต๊ฐ„์—์„œ์˜ ๋ง๋‹จ ์ , ๊ฐ€์ง€ ๊ตฌ์กฐ ๋“ฑ์„ ๋ฐํžŒ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ๋˜ํ•œ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ ๊ธฐ๋ฐ˜์˜ ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„  ๊ฒ€์ถœ์„ ๊ฐ€์†ํ™”ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ์€ ๊ธฐ์ € ๊ณก์„  ๋ฐ ๊ณก๋ฉด์„ ๋‹จ์ˆœํ•œ ๊ธฐํ•˜๋กœ ๊ฐ์‹ธ๊ณ  ๊ธฐํ•˜ ์—ฐ์‚ฐ์„ ์ˆ˜ํ–‰ํ•จ์œผ๋กœ์จ ๊ฐ€์†ํ™”์— ๊ธฐ์—ฌํ•œ๋‹ค. ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„ ์„ ๊ตฌํ•˜๊ธฐ ์œ„ํ•˜์—ฌ, ๋ณธ ๋…ผ๋ฌธ์€ ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ ๊ตฌ์กฐ๋ฅผ ๊ธฐ์ € ๊ณก๋ฉด์˜ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ๊ณผ ๊ธฐ์ € ๊ณก๋ฉด์˜ ๋ฒ•์„  ๊ณก๋ฉด์˜ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ์˜ ๊ตฌ์กฐ๋กœ๋ถ€ํ„ฐ ๊ณ„์‚ฐํ•˜๋ฉฐ ์ด๋•Œ ๊ฐ ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ์˜ ๋‘๊ป˜๋ฅผ ๊ณ„์‚ฐํ•œ๋‹ค. ๋˜ํ•œ, ๋ฐ”์šด๋”ฉ ๋ณผ๋ฅจ ์ค‘์—์„œ ์‹ค์ œ ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ์— ๊ธฐ์—ฌํ•˜์ง€ ์•Š๋Š” ๋ถ€๋ถ„์„ ๊นŠ์€ ์žฌ๊ท€ ์ „์— ์ฐพ์•„์„œ ์ œ๊ฑฐํ•˜๋Š” ์—ฌ๋Ÿฌ ์กฐ๊ฑด๋“ค์„ ๋‚˜์—ดํ•œ๋‹ค. ํ•œํŽธ, ์ž๊ฐ€ ๊ต์ฐจ๊ฐ€ ์ œ๊ฑฐ๋œ ์˜คํ”„์…‹ ๊ณก์„  ๋ฐ ๊ณก๋ฉด์€ ๊ธฐ์ € ๊ณก์„  ๋ฐ ๊ณก๋ฉด์˜ ๋ณด๋กœ๋…ธ์ด ๊ตฌ์กฐ์™€ ๊นŠ์€ ๊ด€๋ จ์ด ์žˆ๋Š” ๊ฒƒ์ด ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ž์œ  ๊ณก๋ฉด์˜ ์—ฐ์†๋œ ์˜คํ”„์…‹ ๊ณก๋ฉด๋“ค๋กœ๋ถ€ํ„ฐ ์ž์œ  ๊ณก๋ฉด์˜ ๋ณด๋กœ๋…ธ์ด ๊ตฌ์กฐ๋ฅผ ์œ ์ถ”ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ํŠนํžˆ, ์˜คํ”„์…‹ ๊ณก๋ฉด์˜ ์ž๊ฐ€ ๊ต์ฐจ ๊ณก์„  ์ƒ์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ๊ฐ€์ง€ ์ ์ด๋‚˜ ๋ง๋‹จ ์ ๊ณผ ๊ฐ™์€ ํŠน์ด์ ๋“ค์ด ์ž์œ  ๊ณก๋ฉด์˜ ๋ณด๋กœ๋…ธ์ด ๊ตฌ์กฐ์—์„œ ์–ด๋–ป๊ฒŒ ํ•ด์„๋˜๋Š”์ง€ ์ œ์‹œํ•œ๋‹ค.1. Introduction 1 1.1 Background and Motivation 1 1.2 Research Objectives and Approach 7 1.3 Contributions and Thesis Organization 11 2. Preliminaries 14 2.1 Curve and Surface Representation 14 2.1.1 Bezier Representation 14 2.1.2 B-spline Representation 17 2.2 Differential Geometry of Curves and Surfaces 19 2.2.1 Differential Geometry of Curves 19 2.2.2 Differential Geometry of Surfaces 21 3. Previous Work 23 3.1 Offset Curves 24 3.2 Offset Surfaces 27 3.3 Offset Curves on Surfaces 29 4. Trimming Offset Curve Self-intersections 32 4.1 Experimental Results 35 5. Trimming Offset Surface Self-intersections 38 5.1 Constraint Equations for Offset Self-Intersections 38 5.1.1 Coplanarity Constraint 39 5.1.2 Equi-angle Constraint 40 5.2 Removing Trivial Solutions 40 5.3 Removing Normal Flips 41 5.4 Multivariate Solver for Constraints 43 5.A Derivation of f(u,v) 46 5.B Relationship between f(u,v) and Curvatures 47 5.3 Trimming Offset Surfaces 50 5.4 Experimental Results 53 5.5 Summary 57 6. Acceleration of trimming offset curves and surfaces 62 6.1 Motivation 62 6.2 Basic Approach 67 6.3 Trimming an Offset Curve using the BVH 70 6.4 Trimming an Offset Surface using the BVH 75 6.4.1 Offset Surface BVH 75 6.4.2 Finding Self-intersections in Offset Surface Using BVH 87 6.4.3 Tracing Self-intersection Curves 98 6.5 Experimental Results 100 6.6 Summary 106 7. Application of Trimming Offset Surfaces: 3D Voronoi Diagram 107 7.1 Background 107 7.2 Approach 110 7.3 Experimental Results 112 7.4 Summary 114 8. Conclusion 119 Bibliography iDocto

    Manufacturability analysis for non-feature-based objects

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    This dissertation presents a general methodology for evaluating key manufacturability indicators using an approach that does not require feature recognition, or feature-based design input. The contributions involve methods for computing three manufacturability indicators that can be applied in a hierarchical manner. The analysis begins with the computation of visibility, which determines the potential manufacturability of a part using material removal processes such as CNC machining. This manufacturability indicator is purely based on accessibility, without considering the actual machine setup and tooling. Then, the analysis becomes more specific by analyzing the complexity in setup planning for the part; i.e. how the part geometry can be oriented to a cutting tool in an accessible manner. This indicator establishes if the part geometry is accessible about an axis of rotation, namely, whether it can be manufactured on a 4th-axis indexed machining system. The third indicator is geometric machinability, which is computed for each machining operation to indicate the actual manufacturability when employing a cutting tool with specific shape and size. The three manufacturability indicators presented in this dissertation are usable as steps in a process; however they can be executed alone or hierarchically in order to render manufacturability information. At the end of this dissertation, a Multi-Layered Visibility Map is proposed, which would serve as a re-design mechanism that can guide a part design toward increased manufacturability
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