Cleaned up notebook
This commit is contained in:
BlueOceanWave committed
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commit
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1 file changed
+104
-206
+104
-206
@@ -9,7 +9,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 81,
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -28,7 +28,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 82,
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -52,15 +52,23 @@
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},
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{
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"cell_type": "code",
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"execution_count": 53,
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"execution_count": 83,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[-243.619306486927, -123.2097721836616, 140.34764917140853, -107.13787698774695, -90.0, 90.0]\n"
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]
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"data": {
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"text/plain": [
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"[-243.619306486927,\n",
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" -123.2097721836616,\n",
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" 140.34764917140853,\n",
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" -107.13787698774695,\n",
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" -90.0,\n",
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" 90.0]"
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]
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},
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"execution_count": 83,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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@@ -80,7 +88,6 @@
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" # Get limbs and offsets\n",
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" offset_x, offset_y, offset_z = (0, 0, 0.14) # Tool offset\n",
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" l_bs, l1, l2, l3, l_wt = (0.1333, .425, .39225, .1267, .0997) # Limb lengths\n",
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" #l3=0.15\n",
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" \n",
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" # Calculate base angle and r relative to shoulder joint\n",
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" def calculate_theta(x, y, a):\n",
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@@ -141,120 +148,37 @@
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" # Return adjusted joint positions\n",
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" return [o+j*i for j, o, i in zip(joints, offsets, inverse)]\n",
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"\n",
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"# print([math.degrees(deg) for deg in get_joints_from_xyz_rel(0.3, 0.3, 0.3)])\n",
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"print([math.degrees(deg) for deg in get_joints_from_xyz_abs(0, -0.3, 0.1)])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 58,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"flip\n",
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"m: -0.9031146536634159\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"47.914345304219715"
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]
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},
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"execution_count": 58,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"def calculate_theta(x, y, a):\n",
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" # Calculate if we need the + or - in our equations\n",
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" if (x>a and y>=0) or (x>-a and y<0):\n",
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" print('no flip')\n",
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" flip = 1\n",
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" elif (x<a and y>=0) or (x<-a and y<0):\n",
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" print('flip')\n",
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" flip = -1\n",
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" else: \n",
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" print('critical')\n",
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" # Critical section (x=a, or x=-a). Infinite slope\n",
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" # Return 0 or 180 depending on sign\n",
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" return math.degrees(math.atan2(y, 0)-math.pi/2)\n",
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" \n",
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" # Calculate tangent line y = mx + b\n",
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" if abs(a) != abs(x): # If there is no division by 0\n",
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" m = (x*y + math.sqrt(x*x*y*y-(x*x-a*a)*(y*y-a*a)))/(x*x-a*a)\n",
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" else: # Deal with edge case when x^2=a^2\n",
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" m = flip*(-a*a+y*y)/(a*y-flip*abs(a*y))\n",
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" \n",
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" print('m:',m)\n",
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" b = flip * a * math.sqrt(1+m*m)\n",
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"\n",
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" # Calculate equivalent tangent point on circle\n",
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" cx = (-flip*m*b)/(1+m*m)\n",
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" cy = m*cx + flip*b\n",
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"\n",
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" # Calculate base angle\n",
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" theta = math.atan2(cy, cx) + (-math.pi if flip==1 else 0)\n",
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"\n",
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" return math.degrees(theta)\n",
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"\n",
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"calculate_theta(-0.1333,0.3,0.1333)"
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"# Print degree rotation for each joint (robot angles)\n",
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"[math.degrees(deg) for deg in get_joints_from_xyz_abs(0, -0.3, 0.1)]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Simulate arm and joint angles"
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"### Simulate Arm and Joint Angles"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 30,
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"execution_count": 84,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Target position (x,y,z): 0.3 0.3 0.3\n",
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"R: 0.4243\n",
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"Angles (base, shoulder, elbow, wrist): [-26.688, 105.6932, 101.1834, 4.5098]\n",
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"Robot Angles: [-116.688, -105.6932, 101.1834, -85.4902, -90.0, 90.0]\n",
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"elbow (x,y): -0.114 0.407\n",
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"wrist (x,y): 0.244 0.435\n",
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"tool (x,y): 0.394 0.435\n"
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]
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},
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{
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"data": {
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"image/png": "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 truncated
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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"outputs": [],
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"source": [
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"def draw_arm(x, y, z):\n",
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"def draw_arm_side_view(x, y, z, details=False):\n",
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"\n",
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" # Get joint angles\n",
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" l1, l2, l3 = (.422864, .359041, .15)\n",
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" offset_x, offset_y, offset_z = (0.145, 0, 0.195)\n",
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" l1, l2, l3 = .425, .39225, .1267\n",
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" offset_x, offset_y, offset_z = (0, 0, 0.14)\n",
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" r, theta = cartesian_to_polar(x, y)\n",
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" base, shoulder, elbow, wrist, _, _ = get_joints_from_xyz_rel(x, y, z)\n",
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"\n",
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" # Print angles\n",
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" print('Target position (x,y,z):', x, y, z)\n",
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" print('R: ', round(math.sqrt(x**2+y**2),4))\n",
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" print('Angles (base, shoulder, elbow, wrist):', [round(math.degrees(i), 4) for i in [base, shoulder, elbow, wrist]])\n",
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" print('Robot Angles:', [round(math.degrees(i), 4) for i in get_joints_from_xyz_abs(x, y, z)])\n",
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" if details:\n",
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" print('Target position (x,y,z):', x, y, z)\n",
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" print('R: ', round(math.sqrt(x**2+y**2),4))\n",
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" print('Angles (base, shoulder, elbow, wrist):', [round(math.degrees(i), 4) for i in [base, shoulder, elbow, wrist]])\n",
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" print('Robot Angles:', [round(math.degrees(i), 4) for i in get_joints_from_xyz_abs(x, y, z)])\n",
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"\n",
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" # Calculate each joint's endpoint position\n",
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" x1, y1 = polar_to_cartesian(l1, shoulder)\n",
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@@ -269,9 +193,10 @@
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" ty = y3 - offset_z\n",
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"\n",
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" # Print each joint's endpoint position\n",
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" print('elbow (x,y):', round(x1,3), round(y1,3))\n",
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" print('wrist (x,y):', round(x2,3), round(y2,3))\n",
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" print('tool (x,y):', round(x3,3), round(y3,3))\n",
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" if details:\n",
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" print('elbow (x,y):', round(x1,3), round(y1,3))\n",
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" print('wrist (x,y):', round(x2,3), round(y2,3))\n",
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" print('tool (x,y):', round(x3,3), round(y3,3))\n",
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"\n",
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" # Draw limbs\n",
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" plt.plot([0, x1], [0, y1], color='cyan', linewidth=7)\n",
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@@ -299,9 +224,7 @@
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" ax = plt.subplot(111)\n",
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" ax.spines[['right', 'top']].set_visible(False)\n",
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" plt.axis('equal')\n",
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" plt.show()\n",
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"\n",
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"draw_arm(0.3, 0.3, 0.3)"
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" plt.show()"
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]
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},
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{
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@@ -310,95 +233,17 @@
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"metadata": {},
|
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"outputs": [],
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"source": [
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"draw_arm(0.3, 0.3, 0.3)\n",
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"draw_arm(-0.3, -0.3, 0.7)\n",
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"draw_arm(-0.3, 0.4, 0.2)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
|
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"## Interactive Arm"
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]
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},
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{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from ipywidgets import interact, FloatSlider\n",
|
||||
"\n",
|
||||
"# Interactive slider for z coordinate\n",
|
||||
"interact(draw_arm, x=FloatSlider(min=0, max=1, step=0.01, value=0.3),\n",
|
||||
" y=FloatSlider(min=0, max=1, step=0.01, value=0.3),\n",
|
||||
" z=FloatSlider(min=0, max=1, step=0.01, value=0.3))\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 66,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Angles: [153.31198894476785, 105.69315886537287, 101.18338602047919, 4.509772844893658, -90.0, 0.0]\n",
|
||||
"(cx, cy): (-0.11909893611698993, 0.0598693027836566)\n",
|
||||
"-0.06746836046451549 0.16257881075200548\n",
|
||||
"-0.24309496877200426 -0.18679793543865197\n",
|
||||
"-0.29999999999998095 -0.29999999999996196\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<Figure size 640x480 with 1 Axes>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Target position (x,y,z): -0.3 -0.3 0.3\n",
|
||||
"R: 0.4243\n",
|
||||
"Angles (base, shoulder, elbow, wrist): [153.312, 105.6932, 101.1834, 4.5098]\n",
|
||||
"Robot Angles: [63.312, -105.6932, 101.1834, -85.4902, -90.0, 90.0]\n",
|
||||
"elbow (x,y): -0.114 0.407\n",
|
||||
"wrist (x,y): 0.244 0.435\n",
|
||||
"tool (x,y): 0.394 0.435\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<Figure size 640x480 with 1 Axes>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"def display_arm(x, y, z):\n",
|
||||
"def draw_arm_top_view(x, y, z, details=False):\n",
|
||||
" # Get joint and position information\n",
|
||||
" angles = get_joints_from_xyz_rel(x, y, z)\n",
|
||||
" print('Angles:', [math.degrees(angle) for angle in angles])\n",
|
||||
"\n",
|
||||
" offset_x, offset_y, offset_z = (0, 0, 0.14) # Tool offset\n",
|
||||
" l_bs, l1, l2, l3, l_wt = (0.1333, .425, .39225, .1267, .0997) # Limb lengths\n",
|
||||
" cx, cy = l_bs*math.cos(angles[0]), l_bs*math.sin(angles[0]) # Base tangent point\n",
|
||||
" line_angle = math.pi/2+angles[0]\n",
|
||||
" print(f'(cx, cy): ({cx}, {cy})')\n",
|
||||
"\n",
|
||||
" if details:\n",
|
||||
" print('Angles:', [round(math.degrees(angle),3) for angle in angles])\n",
|
||||
" print(f'Circle position (cx, cy): ({round(cx, 3)}, {round(cy, 3)})')\n",
|
||||
"\n",
|
||||
"\n",
|
||||
" # Plot coordinate system\n",
|
||||
@@ -425,23 +270,29 @@
|
||||
" # Shoulder\n",
|
||||
" x1, y1 = polar_to_cartesian(l1*math.cos(angles[1]), line_angle)\n",
|
||||
" x1, y1 = cx+x1, cy+y1\n",
|
||||
" print(x1, y1)\n",
|
||||
" z1 = l1*math.sin(angles[1])\n",
|
||||
" plt.plot([cx, x1], [cy, y1], color='cyan', linewidth=3)\n",
|
||||
"\n",
|
||||
" # Elbow\n",
|
||||
" x2, y2 = polar_to_cartesian(l2*math.cos(angles[1]-angles[2]), line_angle)\n",
|
||||
" x2 += x1\n",
|
||||
" y2 += y1\n",
|
||||
" print(x2, y2)\n",
|
||||
" z2 = z1 + l2*math.sin(angles[1]-angles[2])\n",
|
||||
" plt.plot([x1, x2], [y1, y2], color='orange', linewidth=2)\n",
|
||||
"\n",
|
||||
" # Wrist\n",
|
||||
" x3, y3 = polar_to_cartesian(l3*math.cos(angles[1]-angles[2]-angles[3]), line_angle)\n",
|
||||
" x3 += x2\n",
|
||||
" y3 += y2 \n",
|
||||
" print(x3, y3)\n",
|
||||
" y3 += y2\n",
|
||||
" z3 = z2 + l3*math.sin(angles[1]-angles[2]-angles[3]) \n",
|
||||
" plt.plot([x2, x3], [y2, y3], color='red', linewidth=2)\n",
|
||||
"\n",
|
||||
" # Print joint positions\n",
|
||||
" if details:\n",
|
||||
" print(f'Shoulder (x, y, z): ({round(x1,3)}, {round(y1,3)}, {round(z1,3)})')\n",
|
||||
" print(f'Elbow (x, y, z): ({round(x2,3)}, {round(y2,3)}, {round(z2,3)})')\n",
|
||||
" print(f'Wrist (x, y, z): ({round(x3,3)}, {round(y3,3)}, {round(z3,3)})')\n",
|
||||
"\n",
|
||||
" # Display angle\n",
|
||||
" plt.text(0.01, -0.01-cy/abs(cy+0.00001)*0.02, f'{round(math.degrees(angles[0]), 2)}°', fontsize=7)\n",
|
||||
"\n",
|
||||
@@ -465,19 +316,66 @@
|
||||
" # Adjust the position of axis labels\n",
|
||||
" plt.xlabel('+x', horizontalalignment='right', x=1.05)\n",
|
||||
" plt.ylabel('+y', verticalalignment='top', rotation=0, y=1.05)\n",
|
||||
" plt.show()\n",
|
||||
"\n",
|
||||
" draw_arm(x,y,z)\n",
|
||||
"\n",
|
||||
"display_arm(-0.3,-0.3,0.3)"
|
||||
" plt.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"execution_count": 89,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Target position (x,y,z): 0.5 0.5 0.3\n",
|
||||
"R: 0.7071\n",
|
||||
"Angles (base, shoulder, elbow, wrist): [-34.1339, 65.0453, 57.0325, 8.0128]\n",
|
||||
"Robot Angles: [-124.1339, -65.0453, 57.0325, -81.9872, -90.0, 90.0]\n",
|
||||
"elbow (x,y): 0.179 0.385\n",
|
||||
"wrist (x,y): 0.568 0.44\n",
|
||||
"tool (x,y): 0.694 0.44\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<Figure size 640x480 with 1 Axes>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Angles: [-34.134, 65.045, 57.033, 8.013, -90.0, 0.0]\n",
|
||||
"Circle position (cx, cy): (0.11, -0.075)\n",
|
||||
"Shoulder (x, y, z): (0.211, 0.074, 0.385)\n",
|
||||
"Elbow (x, y, z): (0.429, 0.395, 0.44)\n",
|
||||
"Wrist (x, y, z): (0.5, 0.5, 0.44)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<Figure size 640x480 with 1 Axes>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"def draw_arm(x, y, z, details=False):\n",
|
||||
" draw_arm_side_view(x,y,z, details=details)\n",
|
||||
" draw_arm_top_view(x,y,z, details=details)\n",
|
||||
"\n",
|
||||
"draw_arm(0.5,0.5,0.3, details=True)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
|
||||
Reference in new issue
Block a user