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+---
+title: Luxonis OAK-1 Camera Integration Guide for ROS Robots
+sidebar_label: Luxonis OAK-1
+keywords:
+ - luxonis
+ - oak-1
+ - rgb
+ - camera
+ - integration
+ - autonomy
+ - leo
+ - example
+description: >-
+ Learn how to connect a Luxonis OAK-1 camera to your Leo Rover and integrate it
+ with the system using ROS.
+# TODO: add an OAK-1 image (render?)
+image: /img/robots/leo/integrations/oak-d/oak-d-ucm.webp
+---
+
+import ImageZoom from '@site/src/components/ImageZoom';
+import LinkButton from '@site/src/components/LinkButton';
+import Product from '@site/src/products/luxonis-oak-1-w-imx378.mdx';
+
+# Luxonis OAK-1 Camera Integration
+
+In this tutorial we will go through the process of connecting a Luxonis OAK-1
+camera to your Leo Rover and integrating it with the system using ROS.
+
+OAK-1 is a compact AI camera for robotic vision that combines a high-resolution
+12MP color sensor with on-device Neural Network inferencing and Computer Vision
+capabilities provided by the built-in Myriad X VPU. Thanks to that, tasks like
+object detection or tracking can run directly on the camera, without putting any
+load on the rover's computer. The camera uses USB-C for both power and USB3
+connectivity. In robotics, cameras like this are commonly used for object
+recognition, visual tracking and many other computer vision applications.
+
+{/* TODO: add an OAK-1 image (or robot with OAK-1) */}
+
+## What to expect?
+
+After completing this tutorial, you will have a Luxonis OAK-1 camera mounted on
+your Leo Rover, and you will be able to access the camera's data through ROS
+topics, such as:
+
+- `/oak/rgb/image_raw` - the RGB image stream,
+- `/oak/rgb/image_raw/compressed` - the compressed RGB image stream,
+- `/oak/rgb/camera_info` - the camera calibration data.
+
+You will also learn how to use the camera's on-device AI capabilities by running
+an object detection example. The image below shows its final result - the camera
+stream with the detected objects marked with bounding boxes, visualized in RViz:
+
+
+
+## Prerequisites
+
+
+
+
+
+
+
+### Referenced products
+
+
+
+## Hardware integration
+
+{/* TODO: add hardware integration */}
+
+## Software integration
+
+The first thing you can do is to make sure your device has the correct
+permissions. To do this, you can add the following rule to the udev service:
+
+```xml title="/etc/udev/rules.d/luxonis.rules"
+SUBSYSTEM=="usb", ATTRS{idVendor}=="03e7", MODE="0666"
+```
+
+Paste this line to `/etc/udev/rules.d/luxonis.rules` file and reload udev rules
+by typing:
+
+```bash
+sudo udevadm control --reload-rules && sudo udevadm trigger
+```
+
+We want the sensor functionality to be available in the ROS ecosystem, so you
+should install a ROS package that provides a node for the camera.
+
+```bash
+sudo apt install ros-${ROS_DISTRO}-depthai-ros
+```
+
+### Modifying the URDF model
+
+As we want to have the camera model visible with the rover model, we need to
+create an URDF file with the OAK included. Package `depthai_descriptions` is
+installed alongside `depthai-ros` and it contains OAK camera models and xacro
+macros that we can easily add (list of available models
+[here](https://github.com/luxonis/depthai-ros/tree/jazzy/depthai_descriptions/urdf/models)).
+We need to include the correct macro to make the camera visible with the robot's
+model. To do that create a new file in `/etc/ros/urdf` directory, and name it
+`oak-1.urdf.xacro`. In this file, include the following content:
+
+```xml title="/etc/ros/urdf/oak-1.urdf.xacro"
+
+
+
+
+
+
+
+```
+
+The `camera_name` property determines the names of the camera's TF frames and
+topics. It has to be set to the same value as the `name` of the camera node that
+we will launch later in this tutorial. The `cam_<>` properties specify the
+camera's position and orientation in reference to the link set in the `parent`
+property. As the `parent` property is set to "base_link", the position of the
+camera is provided in reference to the origin of the Rover.
+
+:::warning
+
+In the file above, the `cam_<>` properties are set to the default values. You
+will have to adjust them to your mounting solution.
+
+:::
+
+Now we have to include our camera model in `robot.urdf.xacro` file - the
+description that is uploaded at boot. Add this line somewhere before the closing
+`` tag.
+
+```xml title="/etc/ros/urdf/robot.urdf.xacro"
+
+```
+
+### Launching camera nodes
+
+To get the image from camera, you need to launch the camera nodes. You can do it
+by using default DepthAI launcher:
+
+```bash
+ros2 launch depthai_ros_driver camera.launch.py
+```
+
+If you want to change the default parameters, you can do it while the node runs
+with the usage of _RQt_:
+
+```bash
+rqt
+```
+
+If you want the changes of parameters to persist across the runs, create a
+`.yaml` configuration file in `/etc/ros`. This example contains configuration
+for OAK-1 camera:
+
+```yaml title="/etc/ros/oak.yaml"
+/oak:
+ ros__parameters:
+ oak.rgb.image_raw.enable_pub_plugins:
+ ['image_transport/raw', 'image_transport/compressed']
+ camera:
+ i_pipeline_type: RGB
+ i_nn_type: none
+ rgb:
+ i_publish_topic: true
+ i_fps: 30.0
+ i_resolution: 1080P
+ i_isp_num: 2
+ i_isp_den: 3
+ i_output_isp: true
+ i_width: 1280
+ i_height: 720
+```
+
+You can modify the parameters in the file according to your needs and then
+launch:
+
+```bash
+ros2 launch depthai_ros_driver camera.launch.py params_file:=/etc/ros/oak.yaml
+```
+
+:::note
+
+If your OAK-1 unit doesn't have an IMU, you will see this warning:
+
+```
+[WARN] [oak]: IMU enabled but not available!
+```
+
+It is harmless - the driver simply skips creating the IMU node and the camera
+works normally. You can silence it by adding the `pipeline_gen` section to the
+configuration file:
+
+```yaml
+/oak:
+ ros__parameters:
+ pipeline_gen:
+ i_enable_imu: false
+```
+
+:::
+
+:::info
+
+For more information about oak configuration and usage examples you can check
+out the
+[depthai-ros github repository](https://github.com/luxonis/depthai-ros/tree/jazzy).
+
+:::
+
+### (Optional) Launching camera nodes on system startup
+
+To launch camera nodes with the created parameters file on system startup,
+create a launch file in `/etc/ros`:
+
+```xml title="/etc/ros/oak.launch.xml"
+
+
+
+
+
+
+```
+
+:::info
+
+You can set the `namespace` property of the `node` tag to whatever you want, but
+the `name` has to be set to the same value as the `camera_name` in urdf file.
+It's required for the camera data to be placed in correct TF frame.
+
+:::
+
+Then in `/etc/ros/robot.launch.xml` add this line somewhere before the closing
+`` tag:
+
+```xml title="/etc/ros/robot.launch.xml"
+
+```
+
+Now your OAK-1 camera ROS node will start at launch. You can also start them now
+by typing
+
+```bash
+ros-nodes-restart
+```
+
+## Example usage
+
+One of the capabilities of Luxonis OAK-1 Camera is running object detection
+directly on the camera. To test it, we will run one of the `depthai_filters`
+examples.
+
+:::note
+
+If you enabled launching the camera nodes on system startup, disable them now,
+as the example starts its own camera node and two nodes can't connect to the
+same device. To do so, remove the ``
+line from `/etc/ros/robot.launch.xml` and restart ROS2 nodes:
+
+```bash
+ros-nodes-restart
+```
+
+:::
+
+Firstly, we need to modify the OAK parameters file to enable the neural network
+on the camera and pass through the image the network runs on:
+
+```yaml title="/etc/ros/oak.yaml"
+/oak:
+ ros__parameters:
+ oak.rgb.image_raw.enable_pub_plugins:
+ ['image_transport/raw', 'image_transport/compressed']
+ camera:
+ i_pipeline_type: RGB
+ i_nn_type: rgb
+ rgb:
+ i_publish_topic: true
+ i_fps: 30.0
+ i_resolution: 1080P
+ i_isp_num: 2
+ i_isp_den: 3
+ i_output_isp: true
+ i_width: 1280
+ i_height: 720
+ nn:
+ i_enable_passthrough: true
+ i_disable_resize: false
+```
+
+Then run the example, passing the modified parameters file:
+
+```bash
+ros2 launch depthai_filters example_det2d_overlay.launch.py params_file:=/etc/ros/oak.yaml
+```
+
+Now you can switch to the PC connected to rover's access point and run RViz:
+
+```bash
+rviz2
+```
+
+In the RViz window add the visualization by selecting Image from `/overlay`
+topic and clicking OK:
+
+
+
+After doing so, you should be able to see the image from the camera with the
+bounding boxes and names of the detected objects, along with the confidence of
+each detection shown as a percentage:
+
+
+
+The example uses the default detection network - a MobileNet-SSD model trained
+on the PASCAL VOC dataset. It can detect 20 classes of objects, such as person,
+car, bicycle, dog or bottle. You can find the full list of the detected classes
+in the
+[label map](https://github.com/luxonis/depthai-ros/blob/jazzy/depthai_filters/include/depthai_filters/detection2d_overlay.hpp)
+of the overlay node. To learn more about this and other examples from the
+`depthai_filters` package, check out its
+[documentation](https://github.com/luxonis/depthai-ros/tree/jazzy/depthai_filters).
+
+## What's next?
+
+With the camera image available on ROS topics, you can use it in projects
+involving computer vision.
+
+The OAK-1 can run neural network inference directly on the camera. To learn more
+about the camera's capabilities, check out the
+[Luxonis documentation](https://docs.luxonis.com/hardware/products/OAK-1%20W),
+and for more advanced configuration of the ROS driver, see the
+[DepthAI ROS documentation](https://docs.luxonis.com/software/ros/depthai-ros/).
diff --git a/src/products/luxonis-oak-1-w-imx378.mdx b/src/products/luxonis-oak-1-w-imx378.mdx
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+import ProductPreview from '@site/src/components/ProductPreview';
+
+
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