Automated Unsupervised 3D Tool-Path Generation Using Stacked 2D Image Processing Technique
Abstract
1. Introduction
2. State of the Art
3. Materials and Methods
3.1. Geometric Modeling and Parameter Identification
3.2. Model Segmentation and Reconstruction
Algorithm 1: Pseudocode for voxelization as a binary logic |
grid_data = zeros(rx,ry,rz); |
P0 = Facet position |
Nf = Array for normal facets |
for nz = 1 : rz |
for ny = 1 : ry |
for nx = 1 : rx |
% Get the point |
p = [ xa(nx) ; ya(ny) ; za(nz) ]; |
% Find the closest Facet |
vertices_distance = ∑(([ P0(1,:)-p(1) ; P0(2,:)-p(2) ; P0(3,:)-p(3) ])2); |
[v,ind] = min(vertices_distance); |
% Add Point if it is enclosed inside an object |
data = dot(N_f(:,ind),p-P0(:,ind)); |
grid_data(nx,ny,nz) = (data>=0);% logical array size of NxMxK |
end |
end |
end |
3.3. Point Cloud Generation Using Image Processing Techniques
3.4. Tool Path Motion Parameters
3.5. Tool-Path Generation and Parsing
Algorithm 2: Pseudocode for image processed path generator | |
[z,x] = pixels data from image along(z,x) axis | |
Pcor = []; | % Initializing the dynamic coordinate array |
k = 0; | % Counter |
t = 0; | % Counter |
for i = From Zo to Zf | |
t = t + 1; | % Able to count the number of tool passes |
for j = From Xf to Xo | % Holds true for materials to be removed |
if image(i,j)>0; | |
Pnew = [j,i]; | |
k = k + 1; | % Counts the true pixels to be removed |
else | |
Pnew = []; | % Final product pixels |
end | |
P = Pnew; | |
Pcor = [Pcor;P]; | % Creates a vector of tool path |
end | |
end |
3.6. G-Code Generation
- G00 X45 Y20 Z00: Rapid movement to coordinates of (45, 20, 0)
- G01 X45 Y20 Z00 F3.5: Linear movement to coordinates of (45, 20, 0)
- G02/G03 X45 Y20 R1.0: Circular motion to coordinates of (45, 20) with a radius of 1.0
4. Result and Discussion
5. Conclusions and Future Work
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Parameter | STEP | STL | IGES |
---|---|---|---|
Memory (Bytes) | 16.7 K | 684 | 21.3 K |
3D | Yes | Yes | Yes |
Vertices | 18 | 36 | 18 |
Faces | 6 | 12 | 6 |
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Tuli, T.B.; Cesarini, A. Automated Unsupervised 3D Tool-Path Generation Using Stacked 2D Image Processing Technique. J. Manuf. Mater. Process. 2019, 3, 84. https://doi.org/10.3390/jmmp3040084
Tuli TB, Cesarini A. Automated Unsupervised 3D Tool-Path Generation Using Stacked 2D Image Processing Technique. Journal of Manufacturing and Materials Processing. 2019; 3(4):84. https://doi.org/10.3390/jmmp3040084
Chicago/Turabian StyleTuli, Tadele Belay, and Andrea Cesarini. 2019. "Automated Unsupervised 3D Tool-Path Generation Using Stacked 2D Image Processing Technique" Journal of Manufacturing and Materials Processing 3, no. 4: 84. https://doi.org/10.3390/jmmp3040084
APA StyleTuli, T. B., & Cesarini, A. (2019). Automated Unsupervised 3D Tool-Path Generation Using Stacked 2D Image Processing Technique. Journal of Manufacturing and Materials Processing, 3(4), 84. https://doi.org/10.3390/jmmp3040084