diff --git a/theory/lab06_Trajectories.ipynb b/theory/lab06_Trajectories.ipynb
index 3243ba7ce34791ca479e7e286e91eaefeae4afcd..cd13105b4559b4c00be4c74c87984cd69ed5e159 100644
--- a/theory/lab06_Trajectories.ipynb
+++ b/theory/lab06_Trajectories.ipynb
@@ -96,20 +96,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from lab_functions import *\n",
     "import swift\n",
@@ -126,36 +115,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "75201648863940cdb3614b61736f0c9c",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "interactive(children=(IntSlider(value=-90, description='qs', max=90, min=-90), IntSlider(value=0, description=…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<function __main__.linear_interpolation(qs=-90, qe=0, T=8)>"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "def linear_interpolation(qs=-90, qe=0, T=8):\n",
     "    steps = 20*T\n",
@@ -253,36 +217,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "c2c8faa6117a44698eeda49897e0db71",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "interactive(children=(IntSlider(value=-90, description='qs', max=90, min=-90), IntSlider(value=-20, descriptio…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<function __main__.polynomial_interpolation(qs=-90, qe=-20, dss=0, dse=0, ddss=0, ddse=0, T=8)>"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from lab_functions import *\n",
     "\n",
@@ -325,37 +264,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "scrolled": true,
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "241f6bfded9a4bf2bdbce19d92aec2bb",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "interactive(children=(IntSlider(value=0, description='qs', max=90, min=-90), IntSlider(value=70, description='…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<function __main__.polynomial_interpolation(qs=0, qe=70, dss=0, dse=0, ddss=0, ddse=0, T=8)>"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from lab_functions import *\n",
     "\n",
@@ -410,36 +324,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "0fe120e1ab9345dfbd564ff8283ca25b",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "interactive(children=(IntSlider(value=0, description='xs', max=90), IntSlider(value=20, description='xe', max=…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<function __main__.threed_interpolation(xs=0, xe=20, ys=0, ye=30, zs=0, ze=10, T=8)>"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from lab_functions import *\n",
     "\n",
@@ -475,36 +364,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "121e48a235f94ab2abe47d3978219438",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "interactive(children=(FloatSlider(value=0.6, description='xs', max=0.9, min=-0.9), FloatSlider(value=0.5, desc…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<function __main__.eef_translation(xs=0.6, xe=0.5, ys=0.2, ye=0.4, zs=0.3, ze=0.4, T=8)>"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from lab_functions import *\n",
     "\n",
@@ -585,36 +449,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "57a3822188a0430eadd83cdffb4f2c0b",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "interactive(children=(IntSlider(value=145, description='rs', max=180, min=-180), IntSlider(value=180, descript…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<function __main__.eef_pose(rs=145, re=180, ps=110, pe=40, yas=50, yae=90, xs=0.2, xe=0.4, ys=0.2, ye=0.4, zs=0.2, ze=0.4, T=8)>"
-      ]
-     },
-     "execution_count": 12,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from lab_functions import *\n",
     "\n",
@@ -670,36 +509,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "949608ef4a914c959d8ee2a0c3753735",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "interactive(children=(IntSlider(value=180, description='rs', max=180, min=-180), IntSlider(value=-20, descript…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<function __main__.quat_vs_eul(rs=180, re=-20, ys=20, ye=180, T=8, quaternions=True)>"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from scipy.spatial.transform import Slerp\n",
     "from lab_functions import *\n",
@@ -768,14 +582,12 @@
     "steps = 100\n",
     "tr = rtb.ctraj(T1,T2,steps) # tr is a collection of cartesian poses of size 'steps'\n",
     "\n",
-    "# We load our robot from the toolbox\n",
-    "robot = rtb.models.URDF.UR5()\n",
-    "\n",
     "# We solve the inverse kinematics for the target poses\n",
-    "sol = robot.ikine_LM(tr)\n",
+    "qs = ur5.ikine_LM(tr).q\n",
     "\n",
-    "# Animating the trajectory\n",
-    "robot.plot(sol.q, backend=\"swift\")"
+    "for i in range(steps):\n",
+    "    ur5.q = qs[i,:]\n",
+    "    env.step(0.05)"
    ]
   },
   {