content: Aruco marker update

docs/integrations/software/aruco-tracking.mdx

@@ -25,10 +25,6 @@ vision to support tasks such as localization, mapping, and navigation. These
 visual markers provide a reliable, easily detectable point of reference that
 helps robots perceive and interpret their environment with precision.
 
-In this example, we will use
-[ros_aruco_opencv](https://github.com/fictionlab/ros_aruco_opencv/tree/jazzy)
-package for detecting individual markers.
-
 As sending raw images from the camera via wireless network may be insufficient,
 we will relay all the processing to the Raspberry Pi.
 
@@ -42,7 +38,8 @@ we will relay all the processing to the Raspberry Pi.
 
 ## What to expect?
 
-After this tutorial is completed, you should end up with something like this:
+After this tutorial is completed, you will be able to detect and visualize ArUco
+tags like this:
 
 <div className="video-container">
   <LiteYouTubeEmbed
@@ -74,7 +71,10 @@ could use the output in your custom nodes.
 
 ## Software integration
 
-### Installing the packages
+### Starting the ArUco tracking
+
+LeoOS comes with the ArUco tag detection packages preinstalled, so you don't
+need to install anything - they just need to be enabled.
 
 Start by logging in into your rover via SSH:
 
@@ -85,86 +85,40 @@ Start by logging in into your rover via SSH:
   terminal using Putty or OpenSSH."
 />
 
-Install `aruco-opencv` package:
+Start ArUco tracking by setting the corresponding environment variable to `true`
+in `/etc/ros/setup.bash`:
 
-```bash
-sudo apt install ros-${ROS_DISTRO}-aruco-opencv
+```bash title="/etc/ros/setup.bash"
+export START_ARUCO_TRACKING=true
 ```
 
-### Creating launch and configuration files
-
-To launch the tracker, you can use the launch file from the installed
-`aruco-opencv` package or you can create your own. In this guide, we will show
-you how to create a launch file which provides basic config for detecting single
-markers.
-
-In `/etc/ros`, create a `yaml` configuration file. This simple example sets the
-basic parameters for the node.
-
-```yaml title="/etc/ros/tracker.yaml"
-/**:
-  ros__parameters:
-    cam_base_topic: camera/image_color
-    output_frame: 'base_link'
+And restart the ROS nodes:
 
-    marker_dict: 4X4_50
-
-    publish_tf: true
-    marker_size: 0.15
-
-    aruco:
-      adaptiveThreshWinSizeMin: 3
-      adaptiveThreshWinSizeMax: 23
-      adaptiveThreshWinSizeStep: 10
+```bash
+ros-nodes-restart
 ```
 
 :::info
 
-You will most likely need to change marker_size parameter depending on the
-actual size of your printed ArUco tag.
+ArUco tracker configuration can be found in `/etc/ros/aruco_tracker.yaml`. By
+default it is configured to track markers from `4X4_50` ArUco dictionary with
+marker side size of 15cm. If you plan to use different sizes or dictionaries for
+your ArUco markers, `/etc/ros/aruco_tracker.yaml` has to be adjusted
+appropriately.
 
-The parameters in `aruco` namespace are dynamic reconfigure parameters - which
-means you can change them as the node is working using `rqt` (in
-`dynamic reconfigure` plugin). You can play with their values and then add
-chosen parameters to the `yaml` file.
+The parameters in the `aruco` namespace can be changed at runtime while the node
+is working - either with `ros2 param set` or using the `rqt_reconfigure` GUI
+tool. Feel free to play around with different configurations and then add the
+chosen parameters to the `/etc/ros/aruco_tracker.yaml` file.
 
 You can find a detailed description of each parameter in the `aruco` namespace
 [here](https://docs.opencv.org/4.6.0/d5/dae/tutorial_aruco_detection.html).
 
 :::
 
-Next, also in `/etc/ros`, create a launch file that will use the previously
-added configuration with the tracker node.
-
-```xml title="/etc/ros/tracker.launch.xml"
-<launch version="0.1.1">
-  <node pkg="aruco_opencv" exec="aruco_tracker_autostart">
-    <param from="/etc/ros/tracker.yaml" />
-  </node>
-</launch>
-```
-
-Now you can run the tracker with this command:
-
-```bash
-ros2 launch /etc/ros/tracker.launch.xml
-```
-
-or you can include your launch file in the `robot.launch.xml` file so that the
-node will start at boot. To do so, put this line somewhere before the closing
-`</launch>` tag.
-
-```xml title="/etc/ros/robot.launch.xml"
-<include file="/etc/ros/tracker.launch.xml"/>
-```
-
-Now you need to reboot the rover, or restart the ros nodes
-
-```bash
-ros-nodes-restart
-```
+## Example usage
 
-## Generate ArUco markers
+### Generating ArUco markers
 
 Now, we need to create some markers, so go back to your computer.
 
@@ -247,17 +201,17 @@ Open RViz by typing `rviz2` in the terminal and set Fixed Frame to `base_link`.
 <ImageZoom
   src="/img/robots/leo/integrations/aruco-tracking/rviz-fixed-frame.webp"
   alt="Setting base_link in RViz"
-  width="1365"
-  height="728"
+  width="1854"
+  height="1010"
 />
 
 Now on the Displays panel click **Add** -> **By display type** and search for
-`TF` and click **Ok**.
+`TF` and click **OK**.
 
 <ImageZoom
   src="/img/robots/leo/integrations/aruco-tracking/rviz-add-tf.webp"
-  width="1362"
-  height="727"
+  width="1853"
+  height="1012"
 />
 
 As there are many TF frames for the rover itself, to make it easier to
@@ -268,8 +222,8 @@ check their boxes to make them appear in RViz.
 
 <ImageZoom
   src="/img/robots/leo/integrations/aruco-tracking/rviz-tf-instructions.webp"
-  width="1364"
-  height="730"
+  width="1854"
+  height="1012"
 />
 
 :::tip
@@ -287,24 +241,26 @@ choose `Image` display. Click it and confirm with **Ok**.
 
 <ImageZoom
   src="/img/robots/leo/integrations/aruco-tracking/rviz-aruco-image.webp"
-  width="1365"
-  height="729"
+  width="1853"
+  height="1006"
 />
 
 Your final setup should look more or less like this:
 
 <ImageZoom
   src="/img/robots/leo/integrations/aruco-tracking/rviz-setup-final.webp"
   alt="Adding Marker topic to visualization marker in RViz"
-  width="1365"
-  height="729"
+  width="1853"
+  height="1006"
 />
 
-## What next?
+## What's next?
 
-With this tutorial completed you may be wondering what to do next. Our pick
-would be the [ARTag follower](/leo-rover/1.8/leo-examples/follow-artag).
-However, you can check out other examples from leo_examples repository (like
-[line follower](/leo-rover/1.8/leo-examples/line-follower) and
-[object detection](/leo-rover/1.8/leo-examples/object-detection)). You can also
-check out other integrations from our [Integrations site](/integrations).
+After adding ArUco tag detection capabilities to your robot, you might be
+interested in making the Leo Rover follow the markers. For that, you can check
+out the [follow ArUco marker example](/leo-rover/leo-examples/follow-marker).
+You can also check out other examples from leo_examples repository (like
+[line follower](/leo-rover/leo-examples/line-follower) and
+[object detection](/leo-rover/leo-examples/object-detection)). If you are
+looking to add more sensors to your Leo Rover, take a look at our
+[integrations](/integrations).