laser simulation is not good..

Mapping/circle_fitting/circle_fitting.py

@@ -0,0 +1,149 @@
+"""
+
+Object shape recognition with circle fitting
+
+author: Atsushi Sakai (@Atsushi_twi)
+
+"""
+
+
+import matplotlib.pyplot as plt
+import math
+import random
+import numpy as np
+
+
+def circle_fitting(x, y):
+    """
+    Circle Fitting with least squared
+        input: point x-y positions
+        output  cxe x center position
+                cye y center position
+                re  radius of circle
+                error: prediction error
+    """
+
+    sumx = sum(x)
+    sumy = sum(y)
+    sumx2 = sum([ix ** 2 for ix in x])
+    sumy2 = sum([iy ** 2 for iy in y])
+    sumxy = sum([ix * iy for (ix, iy) in zip(x, y)])
+
+    F = np.array([[sumx2, sumxy, sumx],
+                  [sumxy, sumy2, sumy],
+                  [sumx, sumy, len(x)]])
+
+    G = np.array([[-sum([ix ** 3 + ix * iy ** 2 for (ix, iy) in zip(x, y)])],
+                  [-sum([ix ** 2 * iy + iy ** 3 for (ix, iy) in zip(x, y)])],
+                  [-sum([ix ** 2 + iy ** 2 for (ix, iy) in zip(x, y)])]])
+
+    #  try:
+    T = np.linalg.inv(F).dot(G)
+    #  except:
+    #  return (0, 0, float("inf"))
+
+    cxe = float(T[0] / -2)
+    cye = float(T[1] / -2)
+    #  print (cxe,cye,T)
+    #  try:
+    re = math.sqrt(cxe**2 + cye**2 - T[2])
+    #  except:
+    #  return (cxe, cye, float("inf"))
+
+    error = sum([np.hypot(cxe - ix, cye - iy) - re for (ix, iy) in zip(x, y)])
+    #  print(error)
+
+    return (cxe, cye, re, error)
+
+
+def get_sample_points(cx, cy, r, angle_reso):
+    x, y, angle, ran = [], [], [], []
+
+    for theta in np.arange(0.0, 2.0 * math.pi, angle_reso):
+        rn = r * random.uniform(1.0, 1.0)
+        nx = cx + rn * math.cos(theta)
+        ny = cy + rn * math.sin(theta)
+        nangle = math.atan2(ny, nx)
+        nr = math.hypot(nx, ny)
+
+        occluded = False
+        for i in range(len(angle)):
+            if abs(angle[i] - nangle) <= angle_reso:
+                if nr >= ran[i]:
+                    occluded = True
+                    break
+
+        if not occluded:
+            x.append(nx)
+            y.append(ny)
+            angle.append(nangle)
+            ran.append(nr)
+
+    return x, y
+
+
+def plot_circle(x, y, size, color="-b"):
+    deg = list(range(0, 360, 5))
+    deg.append(0)
+    xl = [x + size * math.cos(math.radians(d)) for d in deg]
+    yl = [y + size * math.sin(math.radians(d)) for d in deg]
+    plt.plot(xl, yl, color)
+
+
+def main1():
+    print(__file__ + " start!!")
+
+    tcx = 1.0
+    tcy = 2.0
+    tr = 3.0
+    np = 10
+
+    x, y = get_sample_points(tcx, tcy, tr, np)
+
+    cx, cy, r, error = circle_fitting(x, y)
+    print("Error:", error)
+
+    plot_circle(tcx, tcy, tr)
+    plot_circle(cx, cy, r, color="-xr")
+    plt.plot(x, y, "gx")
+
+    plt.axis("equal")
+    plt.show()
+
+
+def main():
+
+    time = 0.0
+    simtime = 10.0
+    dt = 1.0
+
+    cx = -3.0
+    cy = -5.0
+    theta = math.radians(30.0)
+
+    cr = 1.0
+    angle_reso = math.radians(30.0)
+
+    while time <= simtime:
+        time += dt
+
+        cx += math.cos(theta)
+        cy += math.cos(theta)
+
+        x, y = get_sample_points(cx, cy, cr, angle_reso)
+
+        ex, ey, er, error = circle_fitting(x, y)
+        print("Error:", error)
+
+        plt.cla()
+        plt.axis("equal")
+        plt.plot(0.0, 0.0, "*r")
+        plot_circle(cx, cy, cr)
+        plt.plot(x, y, "xr")
+        plot_circle(ex, ey, er, "-r")
+        plt.pause(dt)
+
+
+if __name__ == '__main__':
+    #  main1()
+    main()

Mapping/object_shape_recognition/convex_circle_fitting.py

@@ -1,15 +0,0 @@
-"""
-
-Object shape recognition with convex optimization
-
-author: Atsushi Sakai (@Atsushi_twi)
-
-"""
-
-
-def main():
-    print(__file__ + " start!!")
-
-
-if __name__ == '__main__':
-    main()

Mapping/object_shape_recognition/object_shape_recognition.py

@@ -1,15 +0,0 @@
-"""
-
-Object shape recognition with convex optimization
-
-author: Atsushi Sakai (@Atsushi_twi)
-
-"""
-
-
-def main():
-    print(__file__ + " start!!")
-
-
-if __name__ == '__main__':
-    main()