Software
Image pre-processing
assuming GIMP:
- Push up the contrast
- Image ==> Mode ==> Indexed
- B/W (1 bit palette)
- Dithering: Floyd-Steinberg
Processing code
for the conversion from the image file to the pen tip path
Step by Step:
- Install Processing
- Download and Install toxiclib
- Create a sketch with the code below:
<source lang="javascript"> import toxi.geom.*;
// tsp variables int particleRouteLength; Vec2D[] particles; int[] particleRoute; int maxParticles;
// image variable PImage img;
float millisLastFrame = 0; float frameTime = 0; // scale of the drawing float s = 2.0;
void setup() {
maxParticles = 15000; //img = loadImage("lenna-lg_BW_loRes.png"); //img = loadImage("test.png"); img = loadImage("lenna_BW_loRes2.png"); size(img.width*(int)s, img.height*(int)s); //size(400, 600); // count black pixels int i; maxParticles = 0; for ( int x = 0; x < img.width; x++ ) { for ( int y = 0; y < img.height; y++ ) { i = ( ( y * img.width ) + x ); // getting pixel index if ( img.pixels[i] == color( 0, 0, 0 ) ) { maxParticles++; } } }
println("black dots: " + maxParticles); // allocate and fill points vector particles = new Vec2D[maxParticles]; i = 0; int j = 0; for ( int x = 0; x < img.width; x++ ) { for ( int y = 0; y < img.height; y++ ) { i = ( ( y * img.width ) + x ); if ( img.pixels[i] == color( 0, 0, 0 ) ) { Vec2D p1 = new Vec2D(x, y); particles[j] = p1; j++; } } } millisLastFrame = millis(); initPath(); // initialize path (NN heuristic) for (int l = 0; l < 5; l++ ) { // optimize path with 2-opt heuristic for (int k = 0; k < 5000; k++ ) optimizePath(); // profiling ... frameTime = (millis() - millisLastFrame)/1000; millisLastFrame = millis(); println("Frame time: " + millisLastFrame); } noLoop();
}
void initPath() {
int temp; println("initializing path (NN)"); Vec2D p1, p2; particleRouteLength = maxParticles; // array of free ramaining particles to be queried boolean freeParticles[] = new boolean[maxParticles]; particleRoute = new int[particleRouteLength]; int closestParticle; float distMin; p1 = particles[0]; freeParticles[0] = true; particleRoute[0] = 0; // Nearest neighbor ("Simple, Greedy") algorithm path optimization: int i = 0, j; float dx, dy, distance; while (i < particleRouteLength) { distMin = Float.MAX_VALUE; // re-initialize mimimun distance value closestParticle = 0; // re-initialize closest particle for (j = 0; j < particleRouteLength; j++) { if (freeParticles[j] == false) { p2 = particles[j]; // get next particle to calculate distance dx = p1.x - p2.x; dy = p1.y - p2.y; distance = (float) (dx*dx+dy*dy); // Only looking for closest; do not need sqrt factor! if (distance < distMin) { closestParticle = j; // update the closest particle index distMin = distance; // update the minimum distance value } } } freeParticles[closestParticle] = true; // remove the particle from the ones to be queried particleRoute[i] = closestParticle; //set the next particle in the path i++; // increment while counter } // Initial routing is complete frameTime = (millis() - millisLastFrame)/1000; millisLastFrame = millis(); println("Frame time: " + millisLastFrame);
}
void optimizePath() {
// 2-opt heuristic optimization: // Identify a pair of edges that would become shorter by reversing part of the tour. int temp; //println("optimizing path (2-opt) " ); for (int i = 0; i < 5000; ++i) { // 1000 tests per frame; you can edit this number. int indexA = floor(random(particleRouteLength - 1)); int indexB = floor(random(particleRouteLength - 1)); if (Math.abs(indexA - indexB) < 2) continue; if (indexB < indexA) { // swap A, B. temp = indexB; indexB = indexA; indexA = temp; }
Vec2D a0 = particles[particleRoute[indexA]]; Vec2D a1 = particles[particleRoute[indexA + 1]]; Vec2D b0 = particles[particleRoute[indexB]]; Vec2D b1 = particles[particleRoute[indexB + 1]];
// Original distance: float dx = a0.x - a1.x; float dy = a0.y - a1.y; float distance = (float) (dx*dx+dy*dy); // only a comparison; do not need sqrt factor! dx = b0.x - b1.x; dy = b0.y - b1.y; distance += (float) (dx*dx+dy*dy); // only a comparison; do not need sqrt factor! // Possible shorter distance? dx = a0.x - b0.x; dy = a0.y - b0.y; float distance2 = (float) (dx*dx+dy*dy); // only a comparison; do not need sqrt factor! dx = a1.x - b1.x; dy = a1.y - b1.y; distance2 += (float) (dx*dx+dy*dy); // only a comparison; do not need sqrt factor!
if (distance2 < distance) { // Reverse tour between a1 and b0. int indexhigh = indexB; int indexlow = indexA + 1; while (indexhigh > indexlow) { temp = particleRoute[indexlow]; particleRoute[indexlow] = particleRoute[indexhigh]; particleRoute[indexhigh] = temp; indexhigh--; indexlow++; } } }
}
void draw() {
//image(img, 0, 0); image(img, width*s, height*s); int i = 0; stroke(128, 128, 255); // Stroke color (blue) strokeWeight (.5); // stroke weight println("in draw, n.part : " + particleRouteLength);
// loop the particles drawing a line between successive points for ( i = 0; i < (particleRouteLength - 1); ++i) { Vec2D p1 = particles[particleRoute[i]]; Vec2D p2 = particles[particleRoute[i + 1]]; line(p1.x*s, p1.y*s, p2.x*s, p2.y*s); }
} </source>
Python code
for the low level controller
<source lang="python">
def getStringsLen(pos_xy, halfPullDist, scale):
x2 = (pos_xy[0] * scale)**2 x2b2 = (halfPullDist - pos_xy[0] * scale)**2 y2 = (pos_xy[1] * scale)**2 return [sqrt(x2+y2) , sqrt(x2b2+y2)]
from time import sleep, clock
- import RPi.GPIO as GPIO
from numpy import loadtxt, pi, sqrt, subtract
- load path file
path = loadtxt("path.txt")
- print path
- systems parameters
r_p = 18.0 #............... pulley radius [mm] d_p = 1500.0 #............. pulley distance [mm] d_p05 = d_p * 0.5 #........ half pulley distance [mm] s_a = 3.5 * (2*pi/360) #... step angle [rad]
- drawing parameters
s = 2.0 #.................. drawing scale [-]
- initialize drawing
pos_init = [240, 240] #........................... set initial position vector (x,y) len_curr = getStringsLen(pos_init, d_p05, s) # ..... get initial string
for i in path:
pos_next = i #................................. allocate next position vector len_next = getStringsLen(pos_next, d_p05, s) #. get next strings lengths dl = subtract(len_next, len_curr) #............ get string lengths difference ds = dl/s_a #.................................. compute motor step (same step angles for both motors) print ds
- ___TODO___ debug from here
- i = 0 #........................................ init while loop
- m1Interval = ?? #.............................. compute time interval for stepping motor 1
- m2Interval = ?? #.............................. compute time interval for stepping motor 2
- intMot1 = 0 #.................................. motor 1 step counter
- intMot2 = 0 #.................................. motor 2 step counter
- clockStart = clock() #......................... initialize clock for stepping the motors
- while 1:
- i = i + 1
- if clockStart - clock() > m1Interval * intMot1:
- #setp motor 1
- if clockStart - clock() > m2Interval * intMot2:
- #setp motor 2
</source>