feat: exapod now stands

control.py

@@ -46,36 +46,28 @@ def direct(alpha, beta, gamma):
     - Entrées: alpha, beta, gamma, la cible (radians) des moteurs
     - Sortie: un tableau contenant la position atteinte par le bout de la patte (en mètres)
     """
-    l1, l2, l3 = 45, 65, 87
 
-    """Prend en entrée les angles moteurs et produit la position atteinte"""
-    xp = l1 + math.cos(beta) * l2 + math.cos(beta + gamma) * l3
-    yp = math.sin(beta) * l2 + math.sin(beta + gamma) * l3
-
-    x = math.cos(alpha) * xp
-    y = math.sin(alpha) * xp
-    z = yp
-
-    return x, y, z
+    return 0, 0, 0
 
 
 from math import *
 
 l1h = 0.049
 l1v = 0.032
-l1 = sqrt(l1h ** 2 + l1v ** 2)
+l1 = l1h
 
 l2h = 0.0605
 l2v = 0.02215
 l2 = sqrt(l2h ** 2 + l2v ** 2)
 
-l3h = 0.013
+l3h = 0.012
 l3v = 0.093
 l3 = sqrt(l3h ** 2 + l3v ** 2)
 
 tete_x = 0.095
-patte_x = 0.032
-patte_y = 0.079
+
+patte_y = 0.032
+patte_x = 0.079
 
 
 def inverse(x, y, z):
@@ -92,12 +84,12 @@ def inverse(x, y, z):
     - Sortie: un tableau contenant les 3 positions angulaires cibles (en radians)
     """
     # Dimensions (m)
-
+    z += l1v
 
     theta0 = atan2(y, x)
 
-    l = sqrt((x - l1h*cos(theta0)) ** 2 + (y - l1h*sin(theta0)) ** 2 + (z + l1v) ** 2)
-
+    l = sqrt((sqrt(x ** 2 + y ** 2) - l1) ** 2 + z ** 2)
+    # l = sqrt((x - l1h*cos(theta0)) ** 2 + (y - l1h*sin(theta0)) ** 2 + (z + l1v) ** 2)
 
     param2 = -1 * (-(l ** 2) + l2 ** 2 + l3 ** 2) / (2 * l2 * l3)
 
@@ -114,7 +106,10 @@ def inverse(x, y, z):
 
     theta1 = acos(param1) + asin(z / l)
 
-    return [-theta0, theta1, theta2]
+    # return [-theta0, theta1, theta2]
+    angle1 = atan(l2v / l2h)
+    return [-theta0, theta1 + angle1, theta2 + angle1 - pi / 2 + atan(l3h / l3v)]
+    # return [0, angle1 , angle1 -pi/2 + atan(l3h/l3v)]
 
 
 def draw(t):
@@ -168,20 +163,21 @@ def legs(targets_robot):
 
     targets = [0] * 18
 
-    cos_val = [1, 1, 0, -1, -1, 0]
-    sin_val = [0, 0, 1, 0, 0, -1]
+    cos_val = [0, 0, -1, 0, 0, 1]
+    sin_val = [-1, -1, 0, 1, 1, 0]
 
-    offset_x = [patte_x, patte_x, tete_x, patte_x, patte_x, tete_x]
-    offset_y = [patte_y, patte_y, 0, patte_y, patte_y, 0]
+    offset_x = [-patte_x, -patte_x, -tete_x, -patte_x, -patte_x, -tete_x]
+    offset_y = [patte_y, -patte_y, 0, patte_y, -patte_y, 0]
 
     for i in range(6):
         target_x, target_y, target_z = targets_robot[i]
 
-        target_x = cos_val[i] * target_x + sin_val[i] * target_x
-        target_y = cos_val[i] * target_y + sin_val[i] * target_y
+        target_x_tmp = cos_val[i] * target_x - sin_val[i] * target_y
+        target_y = sin_val[i] * target_x + cos_val[i] * target_y
+        target_x = target_x_tmp
 
-        target_x += patte_x * offset_x[i]
-        target_y += patte_y * offset_y[i]
+        target_x += offset_x[i]
+        target_y += offset_y[i]
 
         alpha, beta, gamma = inverse(target_x, target_y, target_z)
         targets[3 * i] = alpha
@@ -213,30 +209,32 @@ def walkV1(t, speed_x, speed_y, speed_rotation):
     slider_max = 0.200
 
     neutral_position = np.array([
-        [-0.06, 0.06, -0.13],
-        [-0.06, -0.06, -0.13],
-        [0.06, -0.06, -0.13],  # [0.15, 0.15, -0.01],
-        [0.06, 0.06, -0.13]
+        [0.1, 0.15, -0.16],
+        [-0.1, 0.15, -0.16],
+        [-0.2, -0.00, -0.16],
+        [-0.1, -0.15, -0.16],
+        [0.1, -0.15, -0.16],
+        [0.2, 0, -0.16]
     ])
 
     real_position = np.copy(neutral_position)
 
     movement_x = np.array([
         [0.0, 0, 0],
-        [0.06, 0, 0],
-        [-0.06, 0, 0],
+        [0.00, 0, 0],
+        [-0.00, 0, 0],
     ])
 
     movement_y = np.array([
         [0.0, 0, 0],
-        [0, 0.06, 0],
-        [0, -0.06, 0],
+        [0, 0.00, 0],
+        [0, -0.00, 0],
     ])
 
     movement_z = np.array([
-        [0, 0, 0.02],
-        [0, 0, -0.01],
-        [0, 0, -0.01]
+        [0, 0, 0],
+        [0, 0, 0],
+        [0, 0, 0]
     ])
 
     step_duration = np.array([0.05, 0.3, 0.05])