From 1af4057526187dea5f8b6501e6cfaa08ead3890e Mon Sep 17 00:00:00 2001
From: annika <yintingwong@gmail.com>
Date: Tue, 16 Jan 2024 17:35:01 +0100
Subject: [PATCH 01/10] added fixedFrameState.py

---
 src/svea_sensors/launch/localize.launch       |  5 +-
 .../launch/sensors_launch/rtk.launch          | 10 ++-
 src/svea_sensors/scripts/fixedframestate.py   | 89 +++++++++++++++++++
 3 files changed, 101 insertions(+), 3 deletions(-)
 create mode 100755 src/svea_sensors/scripts/fixedframestate.py

diff --git a/src/svea_sensors/launch/localize.launch b/src/svea_sensors/launch/localize.launch
index 5888d2a0..43241647 100644
--- a/src/svea_sensors/launch/localize.launch
+++ b/src/svea_sensors/launch/localize.launch
@@ -89,7 +89,7 @@
         </group>
 
         <!-- Start IMU -->
-        <include file="$(find svea_sensors)/launch/sensors_launch/imu.launch"></include>
+        <!-- <include file="$(find svea_sensors)/launch/sensors_launch/imu.launch"></include> -->
 
         <!-- Start controller -->
         <include file="$(find svea_sensors)/launch/sensors_launch/controller.launch"></include>
@@ -160,4 +160,7 @@
         <remap from="/odometry/filtered"    to="/odometry/filtered/global"/>
         <remap from="/set_pose"             to="/global/set_pose"/>
     </node>
+
+    <node name="fixedframestate" pkg="svea_sensors" type="fixedframestate.py" output="screen"/>
+    
 </launch>
diff --git a/src/svea_sensors/launch/sensors_launch/rtk.launch b/src/svea_sensors/launch/sensors_launch/rtk.launch
index 3e47fc93..8836f0a6 100644
--- a/src/svea_sensors/launch/sensors_launch/rtk.launch
+++ b/src/svea_sensors/launch/sensors_launch/rtk.launch
@@ -16,8 +16,14 @@
     <arg name="port"            default="80"/>  <!-- PORT 8500 is also valid -->
     <arg name="authenticate"    default="true"/>
     <arg name="mountpoint"      default="MSM_GNSS"/>
-    <arg name="username"        default=""/>
-    <arg name="password"        default=""/>
+    <!-- <arg name="username"        default="ITRL03"/> -->
+    <!-- <arg name="password"        default="171488"/> -->
+    <arg name="username"        default="707886204"/>
+    <arg name="password"        default="115544"/>
+    <!-- <arg name="username"        default="708583036"/> -->
+    <!-- <arg name="password"        default="151515"/> -->
+
+    
     <!-- for rtk2go -->
     <!-- <arg name="host"            default="rtk2go.com"/> -->
     <!-- <arg name="port"            default="2101"/> -->
diff --git a/src/svea_sensors/scripts/fixedframestate.py b/src/svea_sensors/scripts/fixedframestate.py
new file mode 100755
index 00000000..5e79f75a
--- /dev/null
+++ b/src/svea_sensors/scripts/fixedframestate.py
@@ -0,0 +1,89 @@
+#!/usr/bin/env python3
+import rospy
+import tf2_ros
+
+import numpy as np
+
+from geopy.distance import geodesic
+
+from std_msgs.msg import Float64
+from sensor_msgs.msg import NavSatFix
+from svea_msgs.msg import VehicleState
+from geometry_msgs.msg import TransformStamped, Vector3, Quaternion
+
+
+class FixedFrameState:
+    def __init__(self):
+        # Initialize node
+        rospy.init_node('FixedFrameState')
+
+        # Subscriber
+        rospy.Subscriber('/gps/filtered', NavSatFix, self.gpsFilteredCallback)
+
+        # Publisher
+        self.FixedFrameState = rospy.Publisher('/FixedFrameState', VehicleState, queue_size=10)
+
+        # Fixed GPS latitude, Longitude
+        self.fixed_gps = (59.350791, 18.067825) #ITRL pose
+
+        # Transformation
+        self.buffer = tf2_ros.Buffer(rospy.Duration(10))
+        self.listener = tf2_ros.TransformListener(self.buffer)
+        self.br = tf2_ros.TransformBroadcaster()
+
+    def run(self):
+        rospy.spin()
+
+    def gpsFilteredCallback(self, msg):
+        filtered_gps = (msg.latitude, msg.longitude)
+        x, y = self.LatLongToXY(filtered_gps)
+        self.StateMsg(msg.header, x,y)
+
+    def LatLongToXY(self, filtered_gps):
+        distance = geodesic(self.fixed_gps, filtered_gps).meters
+
+        bearing = self.CalculateBearing(filtered_gps)
+
+        # Convert bearing and distance to x, y coordinates
+        x = distance * np.sin(np.radians(bearing))
+        y = distance * np.cos(np.radians(bearing))
+
+        return x, y
+
+    def CalculateBearing(self, filtered_gps):
+        lat1 = np.radians(self.fixed_gps[0])
+        lat2 = np.radians(filtered_gps[0])
+        diffLong = np.radians(filtered_gps[1] - self.fixed_gps[1])
+
+        x = np.sin(diffLong) * np.cos(lat2)
+        y = np.cos(lat1) * np.sin(lat2) - (np.sin(lat1) * np.cos(lat2) * np.cos(diffLong))
+
+        initial_bearing = np.arctan2(x, y)
+
+        initial_bearing = np.degrees(initial_bearing)
+        compass_bearing = (initial_bearing + 360) % 360
+
+        return compass_bearing
+    
+    def StateMsg(self, header, x, y):
+        msg = VehicleState()
+        msg.header = header
+        msg.child_frame_id = "base_link_fixed"
+        msg.x = x
+        msg.y = y
+        msg.yaw = 0 
+        msg.v = 0
+        msg.covariance = [0, 0, 0, 0,
+                          0, 0, 0, 0,
+                          0, 0, 0, 0,
+                          0, 0, 0, 0]
+        self.FixedFrameState.publish(msg)
+
+        msgT = TransformStamped()
+        msgT.header = header
+        msgT.child_frame_id = "base_link_fixed"
+        msgT.transform.translation = Vector3(*[x,y,0.0])
+        msgT.transform.rotation = Quaternion(*[0.0, 0.0, 0.0, 1.0])
+        self.br.sendTransform(msgT)
+if __name__ == '__main__':
+    FixedFrameState().run()

From 64ef5c26ee849202f8e9c6dfdd6f90f0d29620f7 Mon Sep 17 00:00:00 2001
From: annika <yintingwong@gmail.com>
Date: Wed, 17 Jan 2024 12:18:39 +0100
Subject: [PATCH 02/10] Added the fixed_gps frame and requirement

---
 requirements.txt                            |  1 +
 src/svea_sensors/scripts/fixedframestate.py | 48 ++++++++++++++-------
 2 files changed, 34 insertions(+), 15 deletions(-)

diff --git a/requirements.txt b/requirements.txt
index adfbcf5f..facdef68 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -11,3 +11,4 @@
 pyserial
 pyubx2
 geopy
+pyproj
\ No newline at end of file
diff --git a/src/svea_sensors/scripts/fixedframestate.py b/src/svea_sensors/scripts/fixedframestate.py
index 5e79f75a..d6012285 100755
--- a/src/svea_sensors/scripts/fixedframestate.py
+++ b/src/svea_sensors/scripts/fixedframestate.py
@@ -5,8 +5,8 @@
 import numpy as np
 
 from geopy.distance import geodesic
+from pyproj import Proj
 
-from std_msgs.msg import Float64
 from sensor_msgs.msg import NavSatFix
 from svea_msgs.msg import VehicleState
 from geometry_msgs.msg import TransformStamped, Vector3, Quaternion
@@ -18,25 +18,40 @@ def __init__(self):
         rospy.init_node('FixedFrameState')
 
         # Subscriber
-        rospy.Subscriber('/gps/filtered', NavSatFix, self.gpsFilteredCallback)
+        rospy.Subscriber('/gps/filtered', NavSatFix, self.GpsFilteredCallback)
 
         # Publisher
-        self.FixedFrameState = rospy.Publisher('/FixedFrameState', VehicleState, queue_size=10)
+        self.FixedFrameState = rospy.Publisher('/fixedgps/state', VehicleState, queue_size=10)
 
         # Fixed GPS latitude, Longitude
-        self.fixed_gps = (59.350791, 18.067825) #ITRL pose
+        self.fixed_gps = rospy.get_param("~fixed_gps", (59.350791, 18.067825))
+        self.show_frame = rospy.get_param("~show_frame", True)
+        # self.fixed_gps = (59.350791, 18.067825) #(latitude, longitude) #ITRL pose
 
         # Transformation
         self.buffer = tf2_ros.Buffer(rospy.Duration(10))
         self.listener = tf2_ros.TransformListener(self.buffer)
         self.br = tf2_ros.TransformBroadcaster()
+        self.static_br = tf2_ros.StaticTransformBroadcaster()
+
+        self.PublishFixedGpsFrame()
 
     def run(self):
         rospy.spin()
 
-    def gpsFilteredCallback(self, msg):
-        filtered_gps = (msg.latitude, msg.longitude)
-        x, y = self.LatLongToXY(filtered_gps)
+    def PublishFixedGpsFrame(self):
+        projection = Proj(proj='utm', zone=34, ellps='WGS84')
+        utm = projection(self.fixed_gps[1], self.fixed_gps[0])
+        FixedGpsFrame = TransformStamped()
+        FixedGpsFrame.header.stamp = rospy.Time.now()
+        FixedGpsFrame.header.frame_id = "utm"
+        FixedGpsFrame.child_frame_id = "Fixed_gps"
+        FixedGpsFrame.transform.translation = Vector3(*[utm[0], utm[1], 0.0])
+        FixedGpsFrame.transform.rotation = Quaternion(*[0.0, 0.0, 0.0, 1.0])
+        self.static_br.sendTransform(FixedGpsFrame)
+    
+    def GpsFilteredCallback(self, msg):
+        x, y = self.LatLongToXY((msg.latitude, msg.longitude))
         self.StateMsg(msg.header, x,y)
 
     def LatLongToXY(self, filtered_gps):
@@ -44,7 +59,6 @@ def LatLongToXY(self, filtered_gps):
 
         bearing = self.CalculateBearing(filtered_gps)
 
-        # Convert bearing and distance to x, y coordinates
         x = distance * np.sin(np.radians(bearing))
         y = distance * np.cos(np.radians(bearing))
 
@@ -68,7 +82,8 @@ def CalculateBearing(self, filtered_gps):
     def StateMsg(self, header, x, y):
         msg = VehicleState()
         msg.header = header
-        msg.child_frame_id = "base_link_fixed"
+        msg.header.frame_id = "Fixed_gps"
+        msg.child_frame_id = "base_link_fixed_gps"
         msg.x = x
         msg.y = y
         msg.yaw = 0 
@@ -79,11 +94,14 @@ def StateMsg(self, header, x, y):
                           0, 0, 0, 0]
         self.FixedFrameState.publish(msg)
 
-        msgT = TransformStamped()
-        msgT.header = header
-        msgT.child_frame_id = "base_link_fixed"
-        msgT.transform.translation = Vector3(*[x,y,0.0])
-        msgT.transform.rotation = Quaternion(*[0.0, 0.0, 0.0, 1.0])
-        self.br.sendTransform(msgT)
+        if self.show_frame:
+            msgT = TransformStamped()
+            msgT.header = header
+            msgT.header.frame_id = "Fixed_gps"
+            msgT.child_frame_id = "base_link_fixed_gps"
+            msgT.transform.translation = Vector3(*[x,y,0.0])
+            msgT.transform.rotation = Quaternion(*[0.0, 0.0, 0.0, 1.0])
+            self.br.sendTransform(msgT)
+
 if __name__ == '__main__':
     FixedFrameState().run()

From c8dd379a4f6553f0c9a2213a8a2a9a6714c9020a Mon Sep 17 00:00:00 2001
From: annika <yintingwong@gmail.com>
Date: Tue, 23 Jan 2024 11:43:05 +0100
Subject: [PATCH 03/10] First commit

---
 src/svea_sensors/params/robot_localization/global_ekf.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/svea_sensors/params/robot_localization/global_ekf.yaml b/src/svea_sensors/params/robot_localization/global_ekf.yaml
index ad412183..983a829e 100644
--- a/src/svea_sensors/params/robot_localization/global_ekf.yaml
+++ b/src/svea_sensors/params/robot_localization/global_ekf.yaml
@@ -48,7 +48,7 @@ odom0_queue_size: 8
 odom0_nodelay: true
 odom0_relative: false
 odom0_differential: false
-odom0_pose_rejection_threshold: 5
+odom0_pose_rejection_threshold: 200
 
 ##########################################
 # BNO055 IMU #############################

From 8d86a18740d95ab637fcf41e0abc3549e3eea916 Mon Sep 17 00:00:00 2001
From: Annika-wyt <yintingwong@gmail.com>
Date: Tue, 23 Jan 2024 11:49:30 +0100
Subject: [PATCH 04/10] added analysis

---
 .gitignore     |    3 +-
 analysis.ipynb | 2980 ++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 2982 insertions(+), 1 deletion(-)
 create mode 100644 analysis.ipynb

diff --git a/.gitignore b/.gitignore
index 946666c3..bbe812a6 100644
--- a/.gitignore
+++ b/.gitignore
@@ -12,4 +12,5 @@ __pycache__/
 src/.vscode/
 
 venv/
-site/
\ No newline at end of file
+site/
+rosbag/
\ No newline at end of file
diff --git a/analysis.ipynb b/analysis.ipynb
new file mode 100644
index 00000000..26211f16
--- /dev/null
+++ b/analysis.ipynb
@@ -0,0 +1,2980 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import rosbag\n",
+    "from std_msgs.msg import String  # Import the message type you expect to read\n",
+    "\n",
+    "# Specify the path to your ROS bag file\n",
+    "bag_path = '/home/annika/ITRL/GPS_frame/rosbag/2024-01-23-11-08-25.bag'\n",
+    "FixedFrameState1 = []\n",
+    "Lat1 = []\n",
+    "Long1 = []\n",
+    "# Open the bag file\n",
+    "with rosbag.Bag(bag_path, 'r') as bag:\n",
+    "    # Iterate through messages in the bag\n",
+    "    for topic, msg, t in bag.read_messages():\n",
+    "        # Process the messages based on the topic\n",
+    "        if topic == '/fixedgps/state':\n",
+    "            FixedFrameState1.append([msg.x,msg.y])\n",
+    "        if topic == '/gps/filtered':\n",
+    "            Lat1.append(msg.latitude)\n",
+    "            Long1.append(msg.longitude)\n",
+    "# Note: Replace '/your/topic' with the actual topic you are interested in\n",
+    "# You also need to import the correct message type for the specified topic\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import rosbag\n",
+    "from std_msgs.msg import String  # Import the message type you expect to read\n",
+    "\n",
+    "# Specify the path to your ROS bag file\n",
+    "bag_path = '/home/annika/ITRL/GPS_frame/rosbag/2024-01-23-11-12-00.bag'\n",
+    "FixedFrameState2 = []\n",
+    "Lat2 = []\n",
+    "Long2 = []\n",
+    "\n",
+    "# Open the bag file\n",
+    "with rosbag.Bag(bag_path, 'r') as bag:\n",
+    "    # Iterate through messages in the bag\n",
+    "    for topic, msg, t in bag.read_messages():\n",
+    "        # Process the messages based on the topic\n",
+    "        if topic == '/fixedgps/state':\n",
+    "            FixedFrameState2.append([msg.x,msg.y])\n",
+    "        if topic == '/gps/filtered':\n",
+    "            Lat2.append(msg.latitude)\n",
+    "            Long2.append(msg.longitude)\n",
+    "# Note: Replace '/your/topic' with the actual topic you are interested in\n",
+    "# You also need to import the correct message type for the specified topic\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x_values1, y_values1 = zip(*FixedFrameState1)\n",
+    "x_values2, y_values2 = zip(*FixedFrameState2)\n",
+    "\n",
+    "# Create a scatter plot for the first set of coordinates\n",
+    "plt.scatter(x_values1, y_values1, marker='o', label='Coordinates 1')\n",
+    "\n",
+    "# Create a scatter plot for the second set of coordinates\n",
+    "plt.scatter(x_values2, y_values2, marker='s', label='Coordinates 2')\n",
+    "\n",
+    "# Add labels and title\n",
+    "plt.xlabel('X-axis')\n",
+    "plt.xlim(10,20)\n",
+    "plt.ylim(5,20)\n",
+    "plt.ylabel('Y-axis')\n",
+    "plt.title('Scatter Plot of Coordinates')\n",
+    "\n",
+    "# Add a legend\n",
+    "plt.legend()\n",
+    "\n",
+    "# Display the plot\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "Mime type rendering requires nbformat>=4.2.0 but it is not installed",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/IPython/core/formatters.py:922\u001b[0m, in \u001b[0;36mIPythonDisplayFormatter.__call__\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    920\u001b[0m method \u001b[38;5;241m=\u001b[39m get_real_method(obj, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprint_method)\n\u001b[1;32m    921\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m method \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 922\u001b[0m     \u001b[43mmethod\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    923\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
+      "File \u001b[0;32m/usr/local/lib/python3.8/dist-packages/plotly/basedatatypes.py:834\u001b[0m, in \u001b[0;36mBaseFigure._ipython_display_\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    831\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mplotly\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mio\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpio\u001b[39;00m\n\u001b[1;32m    833\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m pio\u001b[38;5;241m.\u001b[39mrenderers\u001b[38;5;241m.\u001b[39mrender_on_display \u001b[38;5;129;01mand\u001b[39;00m pio\u001b[38;5;241m.\u001b[39mrenderers\u001b[38;5;241m.\u001b[39mdefault:\n\u001b[0;32m--> 834\u001b[0m     \u001b[43mpio\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshow\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m    835\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    836\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28mrepr\u001b[39m(\u001b[38;5;28mself\u001b[39m))\n",
+      "File \u001b[0;32m/usr/local/lib/python3.8/dist-packages/plotly/io/_renderers.py:396\u001b[0m, in \u001b[0;36mshow\u001b[0;34m(fig, renderer, validate, **kwargs)\u001b[0m\n\u001b[1;32m    391\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    392\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMime type rendering requires ipython but it is not installed\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    393\u001b[0m         )\n\u001b[1;32m    395\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m nbformat \u001b[38;5;129;01mor\u001b[39;00m Version(nbformat\u001b[38;5;241m.\u001b[39m__version__) \u001b[38;5;241m<\u001b[39m Version(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m4.2.0\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[0;32m--> 396\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    397\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMime type rendering requires nbformat>=4.2.0 but it is not installed\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    398\u001b[0m         )\n\u001b[1;32m    400\u001b[0m     ipython_display\u001b[38;5;241m.\u001b[39mdisplay(bundle, raw\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m    402\u001b[0m \u001b[38;5;66;03m# external renderers\u001b[39;00m\n",
+      "\u001b[0;31mValueError\u001b[0m: Mime type rendering requires nbformat>=4.2.0 but it is not installed"
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{\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmapgl\":[{\"type\":\"heatmapgl\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermapbox\":[{\"type\":\"scattermapbox\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenu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                       {\"responsive\": true}                    )                };                            </script>        </div>"
+      ],
+      "text/plain": [
+       "Figure({\n",
+       "    'data': [{'lat': [59.35093418921517, 59.35093398436031, 59.350933935363415,\n",
+       "                      ..., 59.35092965639449, 59.35092965639449, 59.35092965639449],\n",
+       "              'lon': [18.068044270978096, 18.068044399069947, 18.068044429706774,\n",
+       "                      ..., 18.068060547339595, 18.0680605473396, 18.0680605473396],\n",
+       "              'marker': {'size': 10},\n",
+       "              'mode': 'markers',\n",
+       "              'type': 'scattermapbox'},\n",
+       "             {'lat': [59.35089426416136, 59.35089481178939, 59.35089483355297,\n",
+       "                      ..., 59.35092447731162, 59.35092447731162, 59.35092473299392],\n",
+       "              'lon': [18.068049518147564, 18.06804963070863, 18.068049633812763,\n",
+       "                      ..., 18.06807012756447, 18.06807012756447, 18.06807032891735],\n",
+       "              'marker': {'size': 10},\n",
+       "              'mode': 'markers',\n",
+       "              'type': 'scattermapbox'},\n",
+       "             {'lat': [59.350791], 'lon': [18.067825], 'marker': {'size': 10}, 'mode': 'markers', 'type': 'scattermapbox'}],\n",
+       "    'layout': {'mapbox': {'center': {'lat': 59.350791, 'lon': 18.067825}, 'style': 'open-street-map', 'zoom': 18},\n",
+       "               'margin': {'b': 10, 'l': 10, 'r': 10, 't': 10},\n",
+       "               'template': '...'}\n",
+       "})"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import plotly.graph_objects as go\n",
+    "fig = go.Figure(go.Scattermapbox(\n",
+    "            mode = \"markers\",\n",
+    "            lon = Long1,\n",
+    "            lat = Lat1,\n",
+    "            marker = {'size': 10}))\n",
+    "fig.add_trace(go.Scattermapbox(\n",
+    "            mode = \"markers\",\n",
+    "            lon = Long2,\n",
+    "            lat = Lat2,\n",
+    "            marker = {'size': 10}))\n",
+    "fig.add_trace(go.Scattermapbox(\n",
+    "            mode = \"markers\",\n",
+    "            lon = [18.067825],\n",
+    "            lat = [59.350791],\n",
+    "            marker = {'size': 10}))\n",
+    "fig.update_layout(\n",
+    "                margin ={'l':10,'t':10,'b':10,'r':10},\n",
+    "                mapbox = {\n",
+    "                    'center': {'lon': 18.067825, 'lat': 59.350791},\n",
+    "                    'style': \"open-street-map\",\n",
+    "                    'zoom': 18\n",
+    "                    })"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

From 73286a40db1e9c769f922d073d8f6e219ae56e42 Mon Sep 17 00:00:00 2001
From: annika <yintingwong@gmail.com>
Date: Mon, 29 Jan 2024 13:22:27 +0100
Subject: [PATCH 05/10] Separeted into 2 scripts one for publishing the frame,
 one for doing calculation

---
 src/svea_sensors/launch/localize.launch       |   9 +-
 src/svea_sensors/scripts/fixedframestate.py   | 107 ------------------
 src/svea_sensors/scripts/latlong_to_xy.py     |  94 +++++++++++++++
 .../scripts/reference_gps_frame.py            |  57 ++++++++++
 4 files changed, 159 insertions(+), 108 deletions(-)
 delete mode 100755 src/svea_sensors/scripts/fixedframestate.py
 create mode 100755 src/svea_sensors/scripts/latlong_to_xy.py
 create mode 100755 src/svea_sensors/scripts/reference_gps_frame.py

diff --git a/src/svea_sensors/launch/localize.launch b/src/svea_sensors/launch/localize.launch
index 43241647..f58971df 100644
--- a/src/svea_sensors/launch/localize.launch
+++ b/src/svea_sensors/launch/localize.launch
@@ -161,6 +161,13 @@
         <remap from="/set_pose"             to="/global/set_pose"/>
     </node>
 
-    <node name="fixedframestate" pkg="svea_sensors" type="fixedframestate.py" output="screen"/>
+    <node name="reference_gps_frame" pkg="svea_sensors" type="reference_gps_frame.py" output="screen">
+        <rosparam subst_value="true"> 
+            reference_gps: [59.350791, 18.067825]
+        </rosparam>
+    </node>
+
+    <node name="latlong_to_xy" pkg="svea_sensors" type="latlong_to_xy.py" output="screen"/>
+    
     
 </launch>
diff --git a/src/svea_sensors/scripts/fixedframestate.py b/src/svea_sensors/scripts/fixedframestate.py
deleted file mode 100755
index d6012285..00000000
--- a/src/svea_sensors/scripts/fixedframestate.py
+++ /dev/null
@@ -1,107 +0,0 @@
-#!/usr/bin/env python3
-import rospy
-import tf2_ros
-
-import numpy as np
-
-from geopy.distance import geodesic
-from pyproj import Proj
-
-from sensor_msgs.msg import NavSatFix
-from svea_msgs.msg import VehicleState
-from geometry_msgs.msg import TransformStamped, Vector3, Quaternion
-
-
-class FixedFrameState:
-    def __init__(self):
-        # Initialize node
-        rospy.init_node('FixedFrameState')
-
-        # Subscriber
-        rospy.Subscriber('/gps/filtered', NavSatFix, self.GpsFilteredCallback)
-
-        # Publisher
-        self.FixedFrameState = rospy.Publisher('/fixedgps/state', VehicleState, queue_size=10)
-
-        # Fixed GPS latitude, Longitude
-        self.fixed_gps = rospy.get_param("~fixed_gps", (59.350791, 18.067825))
-        self.show_frame = rospy.get_param("~show_frame", True)
-        # self.fixed_gps = (59.350791, 18.067825) #(latitude, longitude) #ITRL pose
-
-        # Transformation
-        self.buffer = tf2_ros.Buffer(rospy.Duration(10))
-        self.listener = tf2_ros.TransformListener(self.buffer)
-        self.br = tf2_ros.TransformBroadcaster()
-        self.static_br = tf2_ros.StaticTransformBroadcaster()
-
-        self.PublishFixedGpsFrame()
-
-    def run(self):
-        rospy.spin()
-
-    def PublishFixedGpsFrame(self):
-        projection = Proj(proj='utm', zone=34, ellps='WGS84')
-        utm = projection(self.fixed_gps[1], self.fixed_gps[0])
-        FixedGpsFrame = TransformStamped()
-        FixedGpsFrame.header.stamp = rospy.Time.now()
-        FixedGpsFrame.header.frame_id = "utm"
-        FixedGpsFrame.child_frame_id = "Fixed_gps"
-        FixedGpsFrame.transform.translation = Vector3(*[utm[0], utm[1], 0.0])
-        FixedGpsFrame.transform.rotation = Quaternion(*[0.0, 0.0, 0.0, 1.0])
-        self.static_br.sendTransform(FixedGpsFrame)
-    
-    def GpsFilteredCallback(self, msg):
-        x, y = self.LatLongToXY((msg.latitude, msg.longitude))
-        self.StateMsg(msg.header, x,y)
-
-    def LatLongToXY(self, filtered_gps):
-        distance = geodesic(self.fixed_gps, filtered_gps).meters
-
-        bearing = self.CalculateBearing(filtered_gps)
-
-        x = distance * np.sin(np.radians(bearing))
-        y = distance * np.cos(np.radians(bearing))
-
-        return x, y
-
-    def CalculateBearing(self, filtered_gps):
-        lat1 = np.radians(self.fixed_gps[0])
-        lat2 = np.radians(filtered_gps[0])
-        diffLong = np.radians(filtered_gps[1] - self.fixed_gps[1])
-
-        x = np.sin(diffLong) * np.cos(lat2)
-        y = np.cos(lat1) * np.sin(lat2) - (np.sin(lat1) * np.cos(lat2) * np.cos(diffLong))
-
-        initial_bearing = np.arctan2(x, y)
-
-        initial_bearing = np.degrees(initial_bearing)
-        compass_bearing = (initial_bearing + 360) % 360
-
-        return compass_bearing
-    
-    def StateMsg(self, header, x, y):
-        msg = VehicleState()
-        msg.header = header
-        msg.header.frame_id = "Fixed_gps"
-        msg.child_frame_id = "base_link_fixed_gps"
-        msg.x = x
-        msg.y = y
-        msg.yaw = 0 
-        msg.v = 0
-        msg.covariance = [0, 0, 0, 0,
-                          0, 0, 0, 0,
-                          0, 0, 0, 0,
-                          0, 0, 0, 0]
-        self.FixedFrameState.publish(msg)
-
-        if self.show_frame:
-            msgT = TransformStamped()
-            msgT.header = header
-            msgT.header.frame_id = "Fixed_gps"
-            msgT.child_frame_id = "base_link_fixed_gps"
-            msgT.transform.translation = Vector3(*[x,y,0.0])
-            msgT.transform.rotation = Quaternion(*[0.0, 0.0, 0.0, 1.0])
-            self.br.sendTransform(msgT)
-
-if __name__ == '__main__':
-    FixedFrameState().run()
diff --git a/src/svea_sensors/scripts/latlong_to_xy.py b/src/svea_sensors/scripts/latlong_to_xy.py
new file mode 100755
index 00000000..b8d60fb5
--- /dev/null
+++ b/src/svea_sensors/scripts/latlong_to_xy.py
@@ -0,0 +1,94 @@
+#!/usr/bin/env python3
+import rospy
+import tf2_ros
+
+import numpy as np
+
+from geopy.distance import geodesic
+
+from sensor_msgs.msg import NavSatFix
+from svea_msgs.msg import VehicleState
+from geometry_msgs.msg import TransformStamped, Vector3, Quaternion
+
+class latlong_to_xy:
+    def __init__(self):
+        # Initialize node
+        rospy.init_node('latlong_to_xy')
+
+        self.reference_gps = (-1, -1)
+
+        # Subscriber
+        rospy.Subscriber('/gps/filtered', NavSatFix, self.vehicle_gps_callback)
+        rospy.Subscriber('/gps/reference_point', NavSatFix, self.reference_gps_callback)
+
+        # Publisher
+        self.RefernceGpsState = rospy.Publisher('/gps/reference_state', VehicleState, queue_size=10)
+
+        # Transformation
+        self.buffer = tf2_ros.Buffer(rospy.Duration(10))
+        self.listener = tf2_ros.TransformListener(self.buffer)
+        self.br = tf2_ros.TransformBroadcaster()
+        self.static_br = tf2_ros.StaticTransformBroadcaster()
+
+    def run(self):
+        rospy.spin()
+
+    def reference_gps_callback(self, msg):
+        if -1 in self.reference_gps:
+            self.reference_gps = (msg.latitude, msg.longitude)
+
+    def vehicle_gps_callback(self, msg):
+        if not -1 in self.reference_gps:
+            x, y = self.LatLongToXY((msg.latitude, msg.longitude))
+            self.StateMsg(msg.header, x,y)
+
+    def LatLongToXY(self, vehicle_gps):
+        distance = geodesic(self.reference_gps, vehicle_gps).meters
+
+        bearing = self.CalculateBearing(vehicle_gps)
+
+        x = distance * np.sin(np.radians(bearing))
+        y = distance * np.cos(np.radians(bearing))
+
+        return x, y
+
+    def CalculateBearing(self, vehicle_gps):
+        lat1 = np.radians(self.reference_gps[0])
+        lat2 = np.radians(vehicle_gps[0])
+        diffLong = np.radians(vehicle_gps[1] - self.reference_gps[1])
+
+        x = np.sin(diffLong) * np.cos(lat2)
+        y = np.cos(lat1) * np.sin(lat2) - (np.sin(lat1) * np.cos(lat2) * np.cos(diffLong))
+
+        initial_bearing = np.arctan2(x, y)
+
+        initial_bearing = np.degrees(initial_bearing)
+        compass_bearing = (initial_bearing + 360) % 360
+
+        return compass_bearing
+    
+    def StateMsg(self, header, x, y):
+        msg = VehicleState()
+        msg.header = header
+        msg.header.frame_id = "Reference_gps"
+        msg.child_frame_id = "base_link_fixed_gps"
+        msg.x = x
+        msg.y = y
+        msg.yaw = 0 
+        msg.v = 0
+        msg.covariance = [0, 0, 0, 0,
+                          0, 0, 0, 0,
+                          0, 0, 0, 0,
+                          0, 0, 0, 0]
+        self.RefernceGpsState.publish(msg)
+
+        msgT = TransformStamped()
+        msgT.header = header
+        msgT.header.frame_id = "Reference_gps"
+        msgT.child_frame_id = "base_link_fixed_gps"
+        msgT.transform.translation = Vector3(*[x,y,0.0])
+        msgT.transform.rotation = Quaternion(*[0.0, 0.0, 0.0, 1.0])
+        self.br.sendTransform(msgT)
+
+if __name__ == '__main__':
+    latlong_to_xy().run()
diff --git a/src/svea_sensors/scripts/reference_gps_frame.py b/src/svea_sensors/scripts/reference_gps_frame.py
new file mode 100755
index 00000000..de9fe4ab
--- /dev/null
+++ b/src/svea_sensors/scripts/reference_gps_frame.py
@@ -0,0 +1,57 @@
+#!/usr/bin/env python3
+import rospy
+import tf2_ros
+
+from pyproj import Proj
+
+from geometry_msgs.msg import TransformStamped, Vector3, Quaternion
+from sensor_msgs.msg import NavSatFix
+
+####################################################
+### Publish the reference gps frame in utm frame ### 
+####################################################
+
+class reference_gps_frame:
+    def __init__(self):
+        # Initialize node
+        rospy.init_node('reference_gps_frame')
+
+        # Reference GPS latitude, Longitude
+        self.reference_gps = rospy.get_param("~reference_gps", [59.350791, 18.067825]) #ITRL
+
+        # Publisher
+        self.reference_gps_publisher = rospy.Publisher('/gps/reference_point', NavSatFix, queue_size=10)
+
+        # Transformation
+        self.buffer = tf2_ros.Buffer(rospy.Duration(10))
+        self.static_br = tf2_ros.StaticTransformBroadcaster()
+
+        # Variables
+        self.rate = rospy.Rate(10)
+        self.seq = 0
+
+    def PublishReferenceGpsFrame(self):
+        projection = Proj(proj='utm', zone=34, ellps='WGS84')
+        utm = projection(self.reference_gps[1], self.reference_gps[0])
+        FixedGpsFrame = TransformStamped()
+        FixedGpsFrame.header.stamp = rospy.Time.now()
+        FixedGpsFrame.header.frame_id = "utm"
+        FixedGpsFrame.child_frame_id = "reference_gps"
+        FixedGpsFrame.transform.translation = Vector3(*[utm[0], utm[1], 0.0])
+        FixedGpsFrame.transform.rotation = Quaternion(*[0.0, 0.0, 0.0, 1.0])
+        self.static_br.sendTransform(FixedGpsFrame)
+
+        reference_msg = NavSatFix()
+        reference_msg.header.stamp = rospy.Time.now()
+        reference_msg.header.frame_id = "utm"
+        reference_msg.latitude = self.reference_gps[0]
+        reference_msg.longitude = self.reference_gps[1]
+        
+        while not rospy.is_shutdown():
+            reference_msg.header.seq = self.seq
+            self.seq += 1
+            self.reference_gps_publisher.publish(reference_msg)
+            self.rate.sleep()
+
+if __name__ == '__main__':
+    reference_gps_frame().PublishReferenceGpsFrame()

From 1b605e566bf4f408b1d1810edc7a261be550ed13 Mon Sep 17 00:00:00 2001
From: annika <yintingwong@gmail.com>
Date: Tue, 30 Jan 2024 10:18:25 +0100
Subject: [PATCH 06/10] updated frame name

---
 src/svea_sensors/scripts/latlong_to_xy.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/svea_sensors/scripts/latlong_to_xy.py b/src/svea_sensors/scripts/latlong_to_xy.py
index b8d60fb5..3fcc4c99 100755
--- a/src/svea_sensors/scripts/latlong_to_xy.py
+++ b/src/svea_sensors/scripts/latlong_to_xy.py
@@ -70,7 +70,7 @@ def CalculateBearing(self, vehicle_gps):
     def StateMsg(self, header, x, y):
         msg = VehicleState()
         msg.header = header
-        msg.header.frame_id = "Reference_gps"
+        msg.header.frame_id = "reference_gps"
         msg.child_frame_id = "base_link_fixed_gps"
         msg.x = x
         msg.y = y
@@ -84,7 +84,7 @@ def StateMsg(self, header, x, y):
 
         msgT = TransformStamped()
         msgT.header = header
-        msgT.header.frame_id = "Reference_gps"
+        msgT.header.frame_id = "reference_gps"
         msgT.child_frame_id = "base_link_fixed_gps"
         msgT.transform.translation = Vector3(*[x,y,0.0])
         msgT.transform.rotation = Quaternion(*[0.0, 0.0, 0.0, 1.0])

From 3c4f7aeb289c81f2050d911a8c81356f63276b92 Mon Sep 17 00:00:00 2001
From: Annika-wyt <yintingwong@gmail.com>
Date: Tue, 30 Jan 2024 10:27:44 +0100
Subject: [PATCH 07/10] cleanup repo for pr

---
 analysis.ipynb | 2980 ------------------------------------------------
 1 file changed, 2980 deletions(-)
 delete mode 100644 analysis.ipynb

diff --git a/analysis.ipynb b/analysis.ipynb
deleted file mode 100644
index 26211f16..00000000
--- a/analysis.ipynb
+++ /dev/null
@@ -1,2980 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import rosbag\n",
-    "from std_msgs.msg import String  # Import the message type you expect to read\n",
-    "\n",
-    "# Specify the path to your ROS bag file\n",
-    "bag_path = '/home/annika/ITRL/GPS_frame/rosbag/2024-01-23-11-08-25.bag'\n",
-    "FixedFrameState1 = []\n",
-    "Lat1 = []\n",
-    "Long1 = []\n",
-    "# Open the bag file\n",
-    "with rosbag.Bag(bag_path, 'r') as bag:\n",
-    "    # Iterate through messages in the bag\n",
-    "    for topic, msg, t in bag.read_messages():\n",
-    "        # Process the messages based on the topic\n",
-    "        if topic == '/fixedgps/state':\n",
-    "            FixedFrameState1.append([msg.x,msg.y])\n",
-    "        if topic == '/gps/filtered':\n",
-    "            Lat1.append(msg.latitude)\n",
-    "            Long1.append(msg.longitude)\n",
-    "# Note: Replace '/your/topic' with the actual topic you are interested in\n",
-    "# You also need to import the correct message type for the specified topic\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import rosbag\n",
-    "from std_msgs.msg import String  # Import the message type you expect to read\n",
-    "\n",
-    "# Specify the path to your ROS bag file\n",
-    "bag_path = '/home/annika/ITRL/GPS_frame/rosbag/2024-01-23-11-12-00.bag'\n",
-    "FixedFrameState2 = []\n",
-    "Lat2 = []\n",
-    "Long2 = []\n",
-    "\n",
-    "# Open the bag file\n",
-    "with rosbag.Bag(bag_path, 'r') as bag:\n",
-    "    # Iterate through messages in the bag\n",
-    "    for topic, msg, t in bag.read_messages():\n",
-    "        # Process the messages based on the topic\n",
-    "        if topic == '/fixedgps/state':\n",
-    "            FixedFrameState2.append([msg.x,msg.y])\n",
-    "        if topic == '/gps/filtered':\n",
-    "            Lat2.append(msg.latitude)\n",
-    "            Long2.append(msg.longitude)\n",
-    "# Note: Replace '/your/topic' with the actual topic you are interested in\n",
-    "# You also need to import the correct message type for the specified topic\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "x_values1, y_values1 = zip(*FixedFrameState1)\n",
-    "x_values2, y_values2 = zip(*FixedFrameState2)\n",
-    "\n",
-    "# Create a scatter plot for the first set of coordinates\n",
-    "plt.scatter(x_values1, y_values1, marker='o', label='Coordinates 1')\n",
-    "\n",
-    "# Create a scatter plot for the second set of coordinates\n",
-    "plt.scatter(x_values2, y_values2, marker='s', label='Coordinates 2')\n",
-    "\n",
-    "# Add labels and title\n",
-    "plt.xlabel('X-axis')\n",
-    "plt.xlim(10,20)\n",
-    "plt.ylim(5,20)\n",
-    "plt.ylabel('Y-axis')\n",
-    "plt.title('Scatter Plot of Coordinates')\n",
-    "\n",
-    "# Add a legend\n",
-    "plt.legend()\n",
-    "\n",
-    "# Display the plot\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "ValueError",
-     "evalue": "Mime type rendering requires nbformat>=4.2.0 but it is not installed",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "File \u001b[0;32m~/.local/lib/python3.8/site-packages/IPython/core/formatters.py:922\u001b[0m, in \u001b[0;36mIPythonDisplayFormatter.__call__\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    920\u001b[0m method \u001b[38;5;241m=\u001b[39m get_real_method(obj, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprint_method)\n\u001b[1;32m    921\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m method \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 922\u001b[0m     \u001b[43mmethod\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    923\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
-      "File \u001b[0;32m/usr/local/lib/python3.8/dist-packages/plotly/basedatatypes.py:834\u001b[0m, in \u001b[0;36mBaseFigure._ipython_display_\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    831\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mplotly\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mio\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpio\u001b[39;00m\n\u001b[1;32m    833\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m pio\u001b[38;5;241m.\u001b[39mrenderers\u001b[38;5;241m.\u001b[39mrender_on_display \u001b[38;5;129;01mand\u001b[39;00m pio\u001b[38;5;241m.\u001b[39mrenderers\u001b[38;5;241m.\u001b[39mdefault:\n\u001b[0;32m--> 834\u001b[0m     \u001b[43mpio\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshow\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m    835\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    836\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;28mrepr\u001b[39m(\u001b[38;5;28mself\u001b[39m))\n",
-      "File \u001b[0;32m/usr/local/lib/python3.8/dist-packages/plotly/io/_renderers.py:396\u001b[0m, in \u001b[0;36mshow\u001b[0;34m(fig, renderer, validate, **kwargs)\u001b[0m\n\u001b[1;32m    391\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    392\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMime type rendering requires ipython but it is not installed\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    393\u001b[0m         )\n\u001b[1;32m    395\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m nbformat \u001b[38;5;129;01mor\u001b[39;00m Version(nbformat\u001b[38;5;241m.\u001b[39m__version__) \u001b[38;5;241m<\u001b[39m Version(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m4.2.0\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[0;32m--> 396\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    397\u001b[0m             \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMime type rendering requires nbformat>=4.2.0 but it is not installed\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    398\u001b[0m         )\n\u001b[1;32m    400\u001b[0m     ipython_display\u001b[38;5;241m.\u001b[39mdisplay(bundle, raw\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m    402\u001b[0m \u001b[38;5;66;03m# external renderers\u001b[39;00m\n",
-      "\u001b[0;31mValueError\u001b[0m: Mime type rendering requires nbformat>=4.2.0 but it is not installed"
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                       {\"template\":{\"data\":{\"histogram2dcontour\":[{\"type\":\"histogram2dcontour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"choropleth\":[{\"type\":\"choropleth\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"histogram2d\":[{\"type\":\"histogram2d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmap\":[{\"type\":\"heatmap\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"heatmapgl\":[{\"type\":\"heatmapgl\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"contourcarpet\":[{\"type\":\"contourcarpet\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"contour\":[{\"type\":\"contour\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"surface\":[{\"type\":\"surface\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]}],\"mesh3d\":[{\"type\":\"mesh3d\",\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}],\"scatter\":[{\"fillpattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2},\"type\":\"scatter\"}],\"parcoords\":[{\"type\":\"parcoords\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolargl\":[{\"type\":\"scatterpolargl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"scattergeo\":[{\"type\":\"scattergeo\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterpolar\":[{\"type\":\"scatterpolar\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"scattergl\":[{\"type\":\"scattergl\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatter3d\":[{\"type\":\"scatter3d\",\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattermapbox\":[{\"type\":\"scattermapbox\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scatterternary\":[{\"type\":\"scatterternary\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"scattercarpet\":[{\"type\":\"scattercarpet\",\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}}}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}]},\"layout\":{\"autotypenumbers\":\"strict\",\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"hovermode\":\"closest\",\"hoverlabel\":{\"align\":\"left\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"bgcolor\":\"#E5ECF6\",\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"ternary\":{\"bgcolor\":\"#E5ECF6\",\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]]},\"xaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"yaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"automargin\":true,\"zerolinewidth\":2},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\",\"gridwidth\":2}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"geo\":{\"bgcolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"subunitcolor\":\"white\",\"showland\":true,\"showlakes\":true,\"lakecolor\":\"white\"},\"title\":{\"x\":0.05},\"mapbox\":{\"style\":\"light\"}}},\"margin\":{\"l\":10,\"t\":10,\"b\":10,\"r\":10},\"mapbox\":{\"center\":{\"lon\":18.067825,\"lat\":59.350791},\"style\":\"open-street-map\",\"zoom\":18}},                        {\"responsive\": true}                    )                };                            </script>        </div>"
-      ],
-      "text/plain": [
-       "Figure({\n",
-       "    'data': [{'lat': [59.35093418921517, 59.35093398436031, 59.350933935363415,\n",
-       "                      ..., 59.35092965639449, 59.35092965639449, 59.35092965639449],\n",
-       "              'lon': [18.068044270978096, 18.068044399069947, 18.068044429706774,\n",
-       "                      ..., 18.068060547339595, 18.0680605473396, 18.0680605473396],\n",
-       "              'marker': {'size': 10},\n",
-       "              'mode': 'markers',\n",
-       "              'type': 'scattermapbox'},\n",
-       "             {'lat': [59.35089426416136, 59.35089481178939, 59.35089483355297,\n",
-       "                      ..., 59.35092447731162, 59.35092447731162, 59.35092473299392],\n",
-       "              'lon': [18.068049518147564, 18.06804963070863, 18.068049633812763,\n",
-       "                      ..., 18.06807012756447, 18.06807012756447, 18.06807032891735],\n",
-       "              'marker': {'size': 10},\n",
-       "              'mode': 'markers',\n",
-       "              'type': 'scattermapbox'},\n",
-       "             {'lat': [59.350791], 'lon': [18.067825], 'marker': {'size': 10}, 'mode': 'markers', 'type': 'scattermapbox'}],\n",
-       "    'layout': {'mapbox': {'center': {'lat': 59.350791, 'lon': 18.067825}, 'style': 'open-street-map', 'zoom': 18},\n",
-       "               'margin': {'b': 10, 'l': 10, 'r': 10, 't': 10},\n",
-       "               'template': '...'}\n",
-       "})"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import plotly.graph_objects as go\n",
-    "fig = go.Figure(go.Scattermapbox(\n",
-    "            mode = \"markers\",\n",
-    "            lon = Long1,\n",
-    "            lat = Lat1,\n",
-    "            marker = {'size': 10}))\n",
-    "fig.add_trace(go.Scattermapbox(\n",
-    "            mode = \"markers\",\n",
-    "            lon = Long2,\n",
-    "            lat = Lat2,\n",
-    "            marker = {'size': 10}))\n",
-    "fig.add_trace(go.Scattermapbox(\n",
-    "            mode = \"markers\",\n",
-    "            lon = [18.067825],\n",
-    "            lat = [59.350791],\n",
-    "            marker = {'size': 10}))\n",
-    "fig.update_layout(\n",
-    "                margin ={'l':10,'t':10,'b':10,'r':10},\n",
-    "                mapbox = {\n",
-    "                    'center': {'lon': 18.067825, 'lat': 59.350791},\n",
-    "                    'style': \"open-street-map\",\n",
-    "                    'zoom': 18\n",
-    "                    })"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}

From 71924a9082748c1c48a52466a2e49373c8d37f88 Mon Sep 17 00:00:00 2001
From: Annika-wyt <yintingwong@gmail.com>
Date: Tue, 30 Jan 2024 10:30:59 +0100
Subject: [PATCH 08/10] cleanup repo for pr

---
 .gitignore                                                | 3 +--
 src/svea_sensors/launch/localize.launch                   | 2 +-
 src/svea_sensors/launch/sensors_launch/rtk.launch         | 8 ++------
 .../params/robot_localization/global_ekf.yaml             | 2 +-
 4 files changed, 5 insertions(+), 10 deletions(-)

diff --git a/.gitignore b/.gitignore
index bbe812a6..946666c3 100644
--- a/.gitignore
+++ b/.gitignore
@@ -12,5 +12,4 @@ __pycache__/
 src/.vscode/
 
 venv/
-site/
-rosbag/
\ No newline at end of file
+site/
\ No newline at end of file
diff --git a/src/svea_sensors/launch/localize.launch b/src/svea_sensors/launch/localize.launch
index f58971df..e5d34a73 100644
--- a/src/svea_sensors/launch/localize.launch
+++ b/src/svea_sensors/launch/localize.launch
@@ -89,7 +89,7 @@
         </group>
 
         <!-- Start IMU -->
-        <!-- <include file="$(find svea_sensors)/launch/sensors_launch/imu.launch"></include> -->
+        <include file="$(find svea_sensors)/launch/sensors_launch/imu.launch"></include>
 
         <!-- Start controller -->
         <include file="$(find svea_sensors)/launch/sensors_launch/controller.launch"></include>
diff --git a/src/svea_sensors/launch/sensors_launch/rtk.launch b/src/svea_sensors/launch/sensors_launch/rtk.launch
index 8836f0a6..9fb8cdfd 100644
--- a/src/svea_sensors/launch/sensors_launch/rtk.launch
+++ b/src/svea_sensors/launch/sensors_launch/rtk.launch
@@ -16,12 +16,8 @@
     <arg name="port"            default="80"/>  <!-- PORT 8500 is also valid -->
     <arg name="authenticate"    default="true"/>
     <arg name="mountpoint"      default="MSM_GNSS"/>
-    <!-- <arg name="username"        default="ITRL03"/> -->
-    <!-- <arg name="password"        default="171488"/> -->
-    <arg name="username"        default="707886204"/>
-    <arg name="password"        default="115544"/>
-    <!-- <arg name="username"        default="708583036"/> -->
-    <!-- <arg name="password"        default="151515"/> -->
+    <arg name="username"        default=""/>
+    <arg name="password"        default=""/>
 
     
     <!-- for rtk2go -->
diff --git a/src/svea_sensors/params/robot_localization/global_ekf.yaml b/src/svea_sensors/params/robot_localization/global_ekf.yaml
index 983a829e..ad412183 100644
--- a/src/svea_sensors/params/robot_localization/global_ekf.yaml
+++ b/src/svea_sensors/params/robot_localization/global_ekf.yaml
@@ -48,7 +48,7 @@ odom0_queue_size: 8
 odom0_nodelay: true
 odom0_relative: false
 odom0_differential: false
-odom0_pose_rejection_threshold: 200
+odom0_pose_rejection_threshold: 5
 
 ##########################################
 # BNO055 IMU #############################

From 08fb210fb206c5420fad3f6b846958e5b8b8a466 Mon Sep 17 00:00:00 2001
From: Annika-wyt <yintingwong@gmail.com>
Date: Tue, 30 Jan 2024 10:31:49 +0100
Subject: [PATCH 09/10] cleanup

---
 src/svea_sensors/launch/sensors_launch/rtk.launch | 2 --
 1 file changed, 2 deletions(-)

diff --git a/src/svea_sensors/launch/sensors_launch/rtk.launch b/src/svea_sensors/launch/sensors_launch/rtk.launch
index 9fb8cdfd..3e47fc93 100644
--- a/src/svea_sensors/launch/sensors_launch/rtk.launch
+++ b/src/svea_sensors/launch/sensors_launch/rtk.launch
@@ -18,8 +18,6 @@
     <arg name="mountpoint"      default="MSM_GNSS"/>
     <arg name="username"        default=""/>
     <arg name="password"        default=""/>
-
-    
     <!-- for rtk2go -->
     <!-- <arg name="host"            default="rtk2go.com"/> -->
     <!-- <arg name="port"            default="2101"/> -->

From 6f6e506a76b11c94fd43c7d1a895cda50b221e24 Mon Sep 17 00:00:00 2001
From: Annika-wyt <yintingwong@gmail.com>
Date: Tue, 30 Jan 2024 10:32:59 +0100
Subject: [PATCH 10/10] cleanup

---
 src/svea_sensors/launch/localize.launch | 10 ----------
 1 file changed, 10 deletions(-)

diff --git a/src/svea_sensors/launch/localize.launch b/src/svea_sensors/launch/localize.launch
index e5d34a73..5888d2a0 100644
--- a/src/svea_sensors/launch/localize.launch
+++ b/src/svea_sensors/launch/localize.launch
@@ -160,14 +160,4 @@
         <remap from="/odometry/filtered"    to="/odometry/filtered/global"/>
         <remap from="/set_pose"             to="/global/set_pose"/>
     </node>
-
-    <node name="reference_gps_frame" pkg="svea_sensors" type="reference_gps_frame.py" output="screen">
-        <rosparam subst_value="true"> 
-            reference_gps: [59.350791, 18.067825]
-        </rosparam>
-    </node>
-
-    <node name="latlong_to_xy" pkg="svea_sensors" type="latlong_to_xy.py" output="screen"/>
-    
-    
 </launch>