diff --git a/inv_kin_testing.ipynb b/inv_kin_testing.ipynb
index 4bd5917..82ca540 100644
--- a/inv_kin_testing.ipynb
+++ b/inv_kin_testing.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -52,15 +52,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 157,
+   "execution_count": 75,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[45.0, 90.70951422006029, 110.71500355039022, -20.005489330329944]\n",
-      "[45.0, -90.70951422006029, 110.71500355039022, -110.00548933032994]\n"
+      "flip\n",
+      "[62.18186071534606, -126.63734509021032, 142.6959710408549, -106.0586259506446]\n"
      ]
     }
    ],
@@ -77,41 +77,126 @@
     "    # Return angle\n",
     "    return normalized_theta\n",
     "\n",
-    "def get_joints_from_xyz_rel(x, y, z, initial_guess = (math.pi/2, math.pi/2, 0), limbs=(.422864, .359041, .092124)):\n",
-    "    # Get polar coordinates of x,y pair\n",
-    "    r, theta = cartesian_to_polar(x, y)\n",
-    "    \n",
-    "    # Get length of each limb\n",
-    "    l1, l2, l3 = limbs\n",
+    "def get_joints_from_xyz_rel(x, y, z, rx=0, ry=0, rz=0, tool_offset=(0.145, 0, 0.14), initial_guess = (math.pi/2, math.pi/2, 0)):\n",
+    "    # Get limbs and offsets\n",
+    "    offset_x, offset_y, offset_z = tool_offset\n",
+    "    l_bs, l1, l2, l3 = (0.14, .422864, .359041, .15)\n",
+    "\n",
+    "    # Calculate base angle and r relative to shoulder joint\n",
+    "    def calculate_theta(x, y, a):\n",
+    "        # Calculate if we need the + or - in our equations\n",
+    "        if (x>-a and y>=0) or (x>a and y<0):\n",
+    "            print('no flip')\n",
+    "            flip = 1\n",
+    "        elif (x<-a and y>=0) or (x<a and y<0):\n",
+    "            print('flip')\n",
+    "            flip = -1\n",
+    "        else: \n",
+    "            print('critical')\n",
+    "            # Critical section (x=a, or x=-a). Infinite slope\n",
+    "            # Return 0 or 180 depending on sign\n",
+    "            return math.atan2(y, 0)\n",
+    "        \n",
+    "        # Calculate tangent line y = mx + b\n",
+    "        m = (x*y - math.sqrt(x*x*y*y-(x*x-a*a)*(y*y-a*a)))/(x*x-a*a)\n",
+    "        b = flip * a * math.sqrt(1+m*m)\n",
+    "\n",
+    "        # Calculate equivalent tangent point on circle\n",
+    "        cx = (-flip*m*b)/(1+m*m)\n",
+    "        cy = m*cx + flip*b\n",
+    "\n",
+    "        # Calculate base angle, make angle negative if flip=1\n",
+    "        theta = math.atan2(cy, cx) + (-math.pi if flip==1 else 0)\n",
+    "\n",
+    "        return theta\n",
     "    \n",
+    "    base_theta = calculate_theta(x, y, l_bs)\n",
+    "    cx, cy = l_bs*math.cos(base_theta), l_bs*math.sin(l_bs)\n",
+    "    r = math.sqrt((x-cx)**2 + (y-cy)**2) - 0.1\n",
+    "\n",
+    "\n",
     "    # Formulas to find out joint positions for (r, z)\n",
     "    def inv_kin_r_z(p):\n",
-    "        a, b, c = p\n",
+    "        a, b, c = p            \n",
     "\n",
     "        return (l1*math.cos(a) + l2*math.cos(a-b) + l3*math.cos(a-b-c) - r, # r\n",
-    "                l1*math.sin(a) + l2*math.sin(a-b) - l3*math.sin(a-b-c) - z,  # z\n",
+    "                l1*math.sin(a) + l2*math.sin(a-b) - l3*math.sin(a-b-c) - (z+offset_z),  # z\n",
     "                a-b-c) # wrist angle\n",
     "\n",
     "\n",
     "    # Normalize angles\n",
-    "    base, shoulder, elbow, wrist = [normalize_degree(deg) for deg in [theta, *fsolve(inv_kin_r_z, initial_guess)]]\n",
+    "    base, shoulder, elbow, wrist1 = [normalize_degree(deg) for deg in [base_theta, *fsolve(inv_kin_r_z, initial_guess)]]\n",
     "\n",
     "    # Return result\n",
-    "    return base, shoulder, elbow, wrist\n",
+    "    return base, shoulder, elbow, wrist1, ry, rz\n",
     "\n",
     "def get_joints_from_xyz_abs(x, y, z):\n",
     "    joints = get_joints_from_xyz_rel(x, y, z)\n",
     "\n",
     "    # Joint offsets\n",
     "    # Base, Shoulder, Elbow, Wrist\n",
-    "    inverse = [1, -1, 1, 1]\n",
-    "    offsets = [0, 0, 0, -math.pi/2]\n",
+    "    inverse = [1, -1, 1, 1, 1, 1]\n",
+    "    offsets = [-math.pi/2, 0, 0, -math.pi/2, -math.pi/2, 0]\n",
     "\n",
     "    # Return adjusted joint positions\n",
     "    return [o+j*i for j, o, i in zip(joints, offsets, inverse)]\n",
     "\n",
-    "print([math.degrees(deg) for deg in get_joints_from_xyz_rel(0.3, 0.3, 0.3)])\n",
-    "print([math.degrees(deg) for deg in get_joints_from_xyz_abs(0.3, 0.3, 0.3)])"
+    "# print([math.degrees(deg) for deg in get_joints_from_xyz_rel(0.3, 0.3, 0.3)])\n",
+    "print([math.degrees(deg) for deg in get_joints_from_xyz_abs(0, -0.3, 0.1)])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "no flip\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "-126.86989764584402"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def calculate_theta(x, y, a):\n",
+    "        # Calculate if we need the + or - in our equations\n",
+    "        if (x>a and y>=0) or (x>-a and y<0):\n",
+    "            print('no flip')\n",
+    "            flip = 1\n",
+    "        elif (x<a and y>=0) or (x<-a and y<0):\n",
+    "            print('flip')\n",
+    "            flip = -1\n",
+    "        else: \n",
+    "            print('critical')\n",
+    "            # Critical section (x=a, or x=-a). Infinite slope\n",
+    "            # Return 0 or 180 depending on sign\n",
+    "            return math.atan2(y, 0)\n",
+    "        \n",
+    "        # Calculate tangent line y = mx + b\n",
+    "        m = (x*y + math.sqrt(x*x*y*y-(x*x-a*a)*(y*y-a*a)))/(x*x-a*a)\n",
+    "        b = flip * a * math.sqrt(1+m*m)\n",
+    "\n",
+    "        # Calculate equivalent tangent point on circle\n",
+    "        cx = (-flip*m*b)/(1+m*m)\n",
+    "        cy = m*cx + flip*b\n",
+    "\n",
+    "        # Calculate base angle\n",
+    "        theta = math.atan2(cy, cx) + (-math.pi if flip==1 else 0)\n",
+    "\n",
+    "        return theta\n",
+    "\n",
+    "calculate_theta(5,-5,1)"
    ]
   },
   {
@@ -123,24 +208,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 164,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "no flip\n",
       "Target position (x,y,z): 0.3 0.3 0.3\n",
-      "Angles (base, shoulder, elbow, wrist): [45.0, 90.7095, 110.715, -20.0055]\n",
-      "Robot Angles: [45.0, -90.7095, 110.715, -110.0055]\n",
-      "elbow (x,y): -0.005 0.423\n",
-      "wrist (x,y): 0.332 0.3\n",
-      "tool  (x,y): 0.424 0.3\n"
+      "Angles (base, shoulder, elbow, wrist): [-25.7322, 113.4225, 127.6133, -14.1908]\n",
+      "no flip\n",
+      "Robot Angles: [-115.7322, -113.4225, 127.6133, -104.1908]\n",
+      "elbow (x,y): -0.168 0.388\n",
+      "wrist (x,y): 0.18 0.3\n",
+      "tool  (x,y): 0.33 0.3\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -153,7 +240,8 @@
     "def draw_arm(x, y, z):\n",
     "\n",
     "    # Get joint angles\n",
-    "    l1, l2, l3 = (.422864, .359041, .092124)\n",
+    "    l1, l2, l3 = (.422864, .359041, .15)\n",
+    "    offset_x, offset_y, offset_z = (0.145, 0, 0.195)\n",
     "    r, theta = cartesian_to_polar(x, y)\n",
     "    base, shoulder, elbow, wrist = get_joints_from_xyz_rel(x, y, z)\n",
     "\n",
@@ -169,7 +257,10 @@
     "    y2 += y1\n",
     "    x3, y3 = polar_to_cartesian(l3, shoulder-elbow-wrist)\n",
     "    x3 += x2\n",
-    "    y3 += y2\n",
+    "    y3 += y2 \n",
+    "    \n",
+    "    tx = x3\n",
+    "    ty = y3 - offset_z\n",
     "\n",
     "    # Print each joint's endpoint position\n",
     "    print('elbow (x,y):', round(x1,3), round(y1,3))\n",
@@ -180,6 +271,10 @@
     "    plt.plot([0, x1], [0, y1], color='cyan', linewidth=7)\n",
     "    plt.plot([x1, x2], [y1, y2], color='orange', linewidth=7)\n",
     "    plt.plot([x2, x2+l3], [y2, y2], color='red', linewidth=7)\n",
+    "    plt.plot()\n",
+    "\n",
+    "    # Draw toolpoint\n",
+    "    plt.plot([x3, tx], [y3, ty], color='black', linewidth=7)\n",
     "\n",
     "    # Display angles\n",
     "    plt.text(0, 0.02, f'{round(math.degrees(shoulder), 2)}°')\n",
@@ -191,8 +286,8 @@
     "    plt.annotate(f'r={round(r,4)}', xy=(x2/2, 0.01), xycoords='data', xytext=(x2/2, 0), textcoords='offset points')\n",
     "\n",
     "    # Display z arrow\n",
-    "    plt.annotate(f'', xy=(x3, 0), xycoords='data', xytext=(x3, y3), textcoords='data', arrowprops={'arrowstyle': '<->'})\n",
-    "    plt.annotate(f'z={round(y2,4)}', xy=(x3+0.01, y2/2), xycoords='data', xytext=(x3/2, 0), textcoords='offset points')\n",
+    "    plt.annotate(f'', xy=(x3, 0), xycoords='data', xytext=(tx, ty), textcoords='data', arrowprops={'arrowstyle': '<->'})\n",
+    "    plt.annotate(f'z={round(ty,4)}', xy=(x3+0.01, y2/2), xycoords='data', xytext=(x3/2, 0), textcoords='offset points')\n",
     "   \n",
     "    # Display plot\n",
     "    ax = plt.subplot(111)\n",
@@ -205,7 +300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 165,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -213,16 +308,16 @@
      "output_type": "stream",
      "text": [
       "Target position (x,y,z): 0.3 0.3 0.3\n",
-      "Angles (base, shoulder, elbow, wrist): [45.0, 90.7095, 110.715, -20.0055]\n",
-      "Robot Angles: [45.0, -90.7095, 110.715, -110.0055]\n",
-      "elbow (x,y): -0.005 0.423\n",
-      "wrist (x,y): 0.332 0.3\n",
-      "tool  (x,y): 0.424 0.3\n"
+      "Angles (base, shoulder, elbow, wrist): [33.9862, 85.2162, 73.3858, 11.8304]\n",
+      "Robot Angles: [33.9862, -85.2162, 73.3858, -78.1696]\n",
+      "elbow (x,y): 0.035 0.421\n",
+      "wrist (x,y): 0.387 0.495\n",
+      "tool  (x,y): 0.537 0.495\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -235,16 +330,25 @@
      "output_type": "stream",
      "text": [
       "Target position (x,y,z): -0.3 -0.3 0.7\n",
-      "Angles (base, shoulder, elbow, wrist): [-135.0, 71.7346, 15.5104, 56.2242]\n",
-      "Robot Angles: [-135.0, -71.7346, 15.5104, -33.7758]\n",
-      "elbow (x,y): 0.133 0.402\n",
-      "wrist (x,y): 0.332 0.7\n",
-      "tool  (x,y): 0.424 0.7\n"
+      "Angles (base, shoulder, elbow, wrist): [-117.3239, 78.0693, 0.0255, 79.0945]\n",
+      "Robot Angles: [-117.3239, -78.0693, 0.0255, -10.9055]\n",
+      "elbow (x,y): 0.087 0.414\n",
+      "wrist (x,y): 0.162 0.765\n",
+      "tool  (x,y): 0.312 0.762\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\nadee\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\scipy\\optimize\\_minpack_py.py:178: RuntimeWarning: The iteration is not making good progress, as measured by the \n",
+      "  improvement from the last ten iterations.\n",
+      "  warnings.warn(msg, RuntimeWarning)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -257,16 +361,16 @@
      "output_type": "stream",
      "text": [
       "Target position (x,y,z): -0.3 0.4 0.2\n",
-      "Angles (base, shoulder, elbow, wrist): [126.8699, 74.2826, 109.5002, -35.2176]\n",
-      "Robot Angles: [126.8699, -74.2826, 109.5002, -125.2176]\n",
-      "elbow (x,y): 0.115 0.407\n",
-      "wrist (x,y): 0.408 0.2\n",
-      "tool  (x,y): 0.5 0.2\n"
+      "Angles (base, shoulder, elbow, wrist): [111.1813, 100.8341, 104.0795, -3.2455]\n",
+      "Robot Angles: [111.1813, -100.8341, 104.0795, -93.2455]\n",
+      "elbow (x,y): -0.079 0.415\n",
+      "wrist (x,y): 0.279 0.395\n",
+      "tool  (x,y): 0.429 0.395\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -290,13 +394,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 160,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5617bc9f737949c4bc84c787ff88ce16",
+       "model_id": "30dd696bcdc14aec9a1d4c17fb4787d4",
        "version_major": 2,
        "version_minor": 0
       },
@@ -313,7 +417,7 @@
        "<function __main__.draw_arm(x, y, z)>"
       ]
      },
-     "execution_count": 160,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/ur5_control.py b/ur5_control.py
index 724e500..0fdecee 100755
--- a/ur5_control.py
+++ b/ur5_control.py
@@ -216,35 +216,65 @@ def normalize_degree(theta):
     # Return angle
     return normalized_theta
 
-def get_joints_from_xyz_rel(x, y, z, initial_guess = (math.pi/2, math.pi/2, 0), limbs=(.422864, .359041, .092124)):
-    # Get polar coordinates of x,y pair
-    r, theta = cartesian_to_polar(x, y)
+
+def get_joints_from_xyz_rel(x, y, z, rx=0, ry=-math.pi/2, rz=0, initial_guess = (math.pi/2, math.pi/2, 0)):
+    # Get limbs and offsets
+    offset_x, offset_y, offset_z = (0, 0, 0.14)     # Tool offset
+    l_bs, l1, l2, l3, l_wt = (0.1333, .425, .39225, .1267, .0997)    # Limb lengths
+    #l3=0.15
     
-    # Get length of each limb
-    l1, l2, l3 = limbs
+    # Calculate base angle and r relative to shoulder joint
+    def calculate_theta(x, y, a):
+        # Calculate if we need the + or - in our equations
+        if (x>-a and y>=0) or (x>a and y<0):
+            flip = 1
+        elif (x<-a and y>=0) or (x<a and y<0):
+            flip = -1
+        else: 
+            # Critical section (x=a, or x=-a). Infinite slope
+            # Return 0 or 180 depending on sign
+            return math.atan2(y, 0)
+        
+        # Calculate tangent line y = mx + b
+        m = (x*y - math.sqrt(x*x*y*y-(x*x-a*a)*(y*y-a*a)))/(x*x-a*a)
+        b = flip * a * math.sqrt(1+m*m)
+
+        # Calculate equivalent tangent point on circle
+        cx = (-flip*m*b)/(1+m*m)
+        cy = m*cx + flip*b
+
+        # Calculate base angle, make angle negative if flip=1
+        theta = math.atan2(cy, cx) + (-math.pi if flip==1 else 0)
+
+        return theta 
     
+    base_theta = calculate_theta(x, y, l_bs)
+    cx, cy = l_bs*math.cos(base_theta), l_bs*math.sin(l_bs)
+    r = math.sqrt((x-cx)**2 + (y-cy)**2) 
+
+
     # Formulas to find out joint positions for (r, z)
     def inv_kin_r_z(p):
-        a, b, c = p
+        a, b, c = p            
 
         return (l1*math.cos(a) + l2*math.cos(a-b) + l3*math.cos(a-b-c) - r, # r
-                l1*math.sin(a) + l2*math.sin(a-b) - l3*math.sin(a-b-c) - z,  # z
+                l1*math.sin(a) + l2*math.sin(a-b) - l3*math.sin(a-b-c) - (l3*math.sin(a-b-c)) - (z + offset_z),  # z
                 a-b-c) # wrist angle
 
 
     # Normalize angles
-    base, shoulder, elbow, wrist = [normalize_degree(deg) for deg in [theta, *fsolve(inv_kin_r_z, initial_guess)]]
+    base, shoulder, elbow, wrist1 = [normalize_degree(deg) for deg in [base_theta, *fsolve(inv_kin_r_z, initial_guess)]]
 
     # Return result
-    return base, shoulder, elbow, wrist
+    return base, shoulder, elbow, wrist1, ry, rz
 
-def get_joints_from_xyz_abs(x, y, z):
-    joints = get_joints_from_xyz_rel(x, y, z)
+def get_joints_from_xyz_abs(x, y, z, rx=0, ry=-math.pi/2, rz=math.pi/2):
+    joints = get_joints_from_xyz_rel(x, y, z, rx, ry, rz)
 
     # Joint offsets
     # Base, Shoulder, Elbow, Wrist
-    inverse = [1, -1, 1, 1]
-    offsets = [0, 0, 0, -math.pi/2]
+    inverse = [1, -1, 1, 1, 1, 1]
+    offsets = [-math.pi/2, 0, 0, -math.pi/2, 0, 0]
 
     # Return adjusted joint positions
     return [o+j*i for j, o, i in zip(joints, offsets, inverse)]
@@ -262,7 +292,7 @@ if __name__ == "__main__":
                0.40002172976662786, 
                0, 
                -3.14152741295329, 
-               0]
+               math.radians(62)]
 
     # time.sleep(.5)
 
@@ -290,14 +320,21 @@ if __name__ == "__main__":
     # set_pos_abs(*home_pose)
 
 
-    angles = get_joints_from_xyz_abs(0.3, 0.3, 0.3)
-    rob.movej([*angles, *rob.getj()[4:]], acc=1, vel=1)
     
-    angles = get_joints_from_xyz_abs(-0.3, -0.3, 0.7)
-    rob.movej([*angles, *rob.getj()[4:]], acc=1, vel=1)
+    angles = get_joints_from_xyz_abs(-0.7, 0, 0)
+    rob.movej(angles, acc=2, vel=2)
+
+    # joints = []
+    # for i in np.linspace(-0.3, -0.7, 50):
+    #     joints.append(get_joints_from_xyz_abs(i, 0, 0))
+    # rob.movejs(joints, acc=2, vel=2)
+
+    # time.sleep(5)
+
+
+    # angles = get_joints_from_xyz_abs(0, -0.6, 0)
+    # rob.movej(angles, acc=2, vel=2)
     
-    angles = get_joints_from_xyz_abs(-0.3, 0.4, 0.2)
-    rob.movej([*angles, *rob.getj()[4:]], acc=1, vel=1)
 
 
     # set_pos_abs(*p1)