Revert "Update setup_robot_localization.rst"

This reverts commit 1e8afe1.

Author: coffinfish

setup_guides/odom/setup_robot_localization.rst

@@ -6,9 +6,9 @@ In this tutorial, we will discuss how various sources of odometry can be fused t
 
 The ``robot_localization`` package is used to provide a fused and locally accurate smooth odometry information from the data provided by ``N`` odometry sensor inputs. These information can be provided to the package through ``nav_msgs/Odometry``, ``sensor_msgs/Imu``, ``geometry_msgs/PoseWithCovarianceStamped``, and ``geometry_msgs/TwistWithCovarianceStamped`` messages.
 
-A usual robot setup consists of at least the wheel encoders and IMU as its odometry sensor sources. When multiple sources are provided to ``robot_localization``, it is able to fuse the odometry information given by the sensors through the use of state estimation nodes. These nodes make use of either an Extended Kalman filter (``ekf_filter_node``) or an Unscented Kalman Filter (``ukf_node``) to implement this fusion. In addition, the package also implements a ``navsat_transform_node`` which transforms geographic coordinates into the robot’s world frame when working with GPS.
+A usual robot setup consists of at least the wheel encoders and IMU as its odometry sensor sources. When multiple sources are provided to ``robot_localization``, it is able to fuse the odometry information given by the sensors through the use of state estimation nodes. These nodes make use of either an Extended Kalman filter (``ekf_node``) or an Unscented Kalman Filter (``ukf_node``) to implement this fusion. In addition, the package also implements a ``navsat_transform_node`` which transforms geographic coordinates into the robot’s world frame when working with GPS.
 
-Fused sensor data is published by the ``robot_localization`` package through the ``odometry/filtered`` and the ``accel/filtered`` topics, if enabled in its configuration. In addition, it can also publish the ``odom`` => ``base_link`` transform on the ``/tf`` topic. Do note that if you followed :ref:`setup_odom_gz`, you will need to remove the /tf bridge in ``bridge_config.yaml`` to get the transforms from ``ekf_filter_node`` instead of Gazebo.
+Fused sensor data is published by the ``robot_localization`` package through the ``odometry/filtered`` and the ``accel/filtered`` topics, if enabled in its configuration. In addition, it can also publish the ``odom`` => ``base_link`` transform on the ``/tf`` topic. Do note that if you followed :ref:`setup_odom_gz`, you will need to remove the /tf bridge in ``bridge_config.yaml`` to get the transforms from ``ekf_node`` instead of Gazebo.
 
 .. seealso::
   More details on ``robot_localization`` can be found in the official `Robot Localization Documentation <http://docs.ros.org/en/noetic/api/robot_localization/html/index.html>`_.
@@ -23,20 +23,20 @@ For the rest of this section, we will show how to use ``robot_localization`` to
 Configuring Robot Localization
 ==============================
 
-Let us now configure the ``robot_localization`` package to use an Extended Kalman Filter (``ekf_filter_node``) to fuse odometry information and publish the ``odom`` => ``base_link`` transform.
+Let us now configure the ``robot_localization`` package to use an Extended Kalman Filter (``ekf_node``) to fuse odometry information and publish the ``odom`` => ``base_link`` transform.
 
 First, install the ``robot_localization`` package using your machines package manager or by executing the following command:
 
 .. code-block:: shell
 
   sudo apt install ros-<ros2-distro>-robot-localization
 
-Next, we specify the parameters of the ``ekf_filter_node`` using a YAML file. Create a directory named ``config`` at the root of your project and create a file named ``ekf.yaml``. Copy the following lines of code into your ``ekf.yaml`` file.
+Next, we specify the parameters of the ``ekf_node`` using a YAML file. Create a directory named ``config`` at the root of your project and create a file named ``ekf.yaml``. Copy the following lines of code into your ``ekf.yaml`` file.
 
 .. code-block:: yaml
 
   ### ekf config file ###
-  ekf_filter_node:
+  ekf_node:
       ros__parameters:
   # The frequency, in Hz, at which the filter will output a position estimate. Note that the filter will not begin
   # computation until it receives at least one message from one of the inputs. It will then run continuously at the
@@ -85,7 +85,7 @@ Next, we specify the parameters of the ``ekf_filter_node`` using a YAML file. Cr
 
 In this configuration, we defined the parameter values of ``frequency``, ``two_d_mode``, ``publish_acceleration``, ``publish_tf``, ``map_frame``, ``odom_frame``, ``base_link_frame``, and ``world_frame``. For more information on the other parameters you can modify, see `Parameters of state estimation nodes <http://docs.ros.org/en/melodic/api/robot_localization/html/state_estimation_nodes.html#parameters>`_, and a sample ``efk.yaml`` can be found `here <https://github.com/cra-ros-pkg/robot_localization/blob/ros2/params/ekf.yaml>`_.
 
-To add a sensor input to the ``ekf_filter_node``, add the next number in the sequence to its base name (odom, imu, pose, twist). In our case, we have one ``nav_msgs/Odometry`` and one ``sensor_msgs/Imu`` as inputs to the filter, thus we use ``odom0`` and ``imu0``. We set the value of ``odom0`` to ``demo/odom``, which is the topic that publishes the ``nav_msgs/Odometry``. Similarly, we set the value of ``imu0`` to the topic that publishes ``sensor_msgs/Imu``, which is ``demo/imu``.
+To add a sensor input to the ``ekf_node``, add the next number in the sequence to its base name (odom, imu, pose, twist). In our case, we have one ``nav_msgs/Odometry`` and one ``sensor_msgs/Imu`` as inputs to the filter, thus we use ``odom0`` and ``imu0``. We set the value of ``odom0`` to ``demo/odom``, which is the topic that publishes the ``nav_msgs/Odometry``. Similarly, we set the value of ``imu0`` to the topic that publishes ``sensor_msgs/Imu``, which is ``demo/imu``.
 
 To understand how ``robot_localization`` is configured and understand the reasoning behind the config have a look at `Configuring robot_localization <http://docs.ros.org/en/melodic/api/robot_localization/html/configuring_robot_localization.html>`_.
 
@@ -96,14 +96,14 @@ To understand how ``robot_localization`` is configured and understand the reason
 Launch and Build Files
 ======================
 
-Now, let us add the ``ekf_filter_node`` into the launch file. Open ``launch/display.launch.py`` and paste the following lines before the ``return launch.LaunchDescription([`` line.
+Now, let us add the ``ekf_node`` into the launch file. Open ``launch/display.launch.py`` and paste the following lines before the ``return launch.LaunchDescription([`` line.
 
 .. code-block:: shell
 
   robot_localization_node = Node(
       package='robot_localization',
-      executable='ekf_filter_node',
-      name='ekf_filter_node',
+      executable='ekf_node',
+      name='ekf_node',
       output='screen',
       parameters=[os.path.join(pkg_share, 'config/ekf.yaml'), {'use_sim_time': LaunchConfiguration('use_sim_time')}]
   )
@@ -175,17 +175,17 @@ You can also check the subscriber count of these topics again by executing:
 
 You should see that ``/demo/imu`` and ``/demo/odom`` now both have 1 subscriber each.
 
-To verify that the ``ekf_filter_node`` are the subscribers of these topics, execute:
+To verify that the ``ekf_node`` are the subscribers of these topics, execute:
 
 .. code-block:: shell
 
-  ros2 node info /ekf_filter_node
+  ros2 node info /ekf_node
 
 You should see an output as shown below.
 
 .. code-block:: shell
 
-  /ekf_filter_node
+  /ekf_node
   Subscribers:
     /demo/imu: sensor_msgs/msg/Imu
     /demo/odom: nav_msgs/msg/Odometry
@@ -201,7 +201,7 @@ You should see an output as shown below.
   Service Servers:
      ...
 
-From the output above, we can see that the ``ekf_filter_node`` is subscribed to ``/demo/imu`` and ``/demo/odom``. We can also see that the ``ekf_filter_node`` publishes on the ``odometry/filtered``, ``accel/filtered``, and ``/tf`` topics.
+From the output above, we can see that the ``ekf_node`` is subscribed to ``/demo/imu`` and ``/demo/odom``. We can also see that the ``ekf_node`` publishes on the ``odometry/filtered``, ``accel/filtered``, and ``/tf`` topics.
 
 You may also verify that ``robot_localization`` is publishing the ``odom`` => ``base_link`` transform by using the tf2_echo utility. Run the following command in a separate command line terminal: