[DOCS] move rvc folder

robotics-ai-suite/robot-vision-control/docs/source/components.rst → robotics-ai-suite/docs/rvc/components.rst

@@ -15,7 +15,7 @@ RVC Framework is composed by
 
 High level design:
 
-.. image:: images/html/RVC.png
+.. image:: ../images/html/RVC.png
 
 .. toctree::
    :maxdepth: 1

robotics-ai-suite/robot-vision-control/docs/source/components/rvc_control.rst → robotics-ai-suite/docs/rvc/components/rvc_control.rst

@@ -6,7 +6,7 @@ Control
 
 .. _High Level Design:
 
-.. image:: images/html/RVCControl.png
+.. image:: ../../images/html/RVCControl.png
    :alt: High Level Design
 
 The above :ref:`High Level Design <High Level Design>` diagram shows in communication between

robotics-ai-suite/robot-vision-control/docs/source/components/rvc_vision/2.5d_vision/2.5d_vision.rst → robotics-ai-suite/docs/rvc/components/rvc_vision/2.5d_vision/2.5d_vision.rst

@@ -12,7 +12,7 @@ This approach uses a standard camera RGB steam together with the camera calibrat
 With Computer Vision methods, the camera stream is scanned for given objects (by sample image).
 A detection is in the form of a 2D bounding box with an additional angle defining the rotation of the object.
 
-.. image:: ../../../images/html/rotatedBB.png
+.. image:: ./../../../../images/html/rotatedBB.png
 
 
 .. note:: 
@@ -31,7 +31,7 @@ Pose Projection
 Additionally, this component is capable of projecting the finding in the flat RGB input image into a 3D object pose.
 Therefor the algorithm projects the object found in the 2D image onto a plane at the given distance and assumes that the object from the image is located on this plane.
 
-.. image:: ../../../images/html/PoseProjection.png
+.. image:: ../../../../../images/html/PoseProjection.png
 
 The above illustration shows the setup and how the camera, the plana and the object relate to each other.
 
@@ -40,7 +40,7 @@ This will be the input for the :ref:`Control<rvc_control>` components to define
 
 Annotated image
 ^^^^^^^^^^^^^^^
-.. image:: ../../../images/html/2.5DAnnotatedImage.png
+.. image:: ../../../../../images/html/2.5DAnnotatedImage.png
 
 The ``rotated_object_detection`` node can produce an annotated image as output. This is useful to visually inspect the detections.
 

robotics-ai-suite/robot-vision-control/docs/source/components/rvc_vision/dynamic_vision.rst → robotics-ai-suite/docs/rvc/components/rvc_vision/dynamic_vision.rst

@@ -24,7 +24,7 @@ The component of this container are:
 
 .. _vision_container_high_level_diagram:
 
-.. image:: images/html/RVCVisionHighLevel.png
+.. image:: ../../../images/html/RVCVisionHighLevel.png
     :alt: Vision container high level diagram
 
 

robotics-ai-suite/robot-vision-control/docs/source/index.rst → robotics-ai-suite/docs/rvc/index.rst

@@ -4,7 +4,7 @@
 Stationary Robot Vision & Control
 ######################################
 
-.. image:: images/html/robotic-arm-graphic.png
+.. image:: ../images/html/robotic-arm-graphic.png
 
 Robotics Pick and Place in Industrial Fields
 ============================================
@@ -54,7 +54,7 @@ Robot Vision and Control aims at tackling the problematics and offers a flexible
 Robot Vision and Control is a robotic software framework aimed at tackling Pick and place, Track
 and place industrial problems.
 
-.. image:: images/html/RobotBackground.png
+.. image:: ../images/html/RobotBackground.png
 
 
 Stationary Robot Vision & Control Resources

robotics-ai-suite/robot-vision-control/docs/source/use_cases/dynamic_use_case/state_machine_node.rst → robotics-ai-suite/docs/rvc/use_cases/dynamic_use_case/state_machine_node.rst

@@ -150,13 +150,13 @@ the two, here is the conversion:
 
 
 
-.. image:: images/html/convertWaypoint.png
+.. image:: ../../../images/html/convertWaypoint.png
     :alt: UR External Control
 
 1. Assure that the drop down ``Feature`` is set to ``base``
 2. Assure that the TCP offset takes in account how far the gripper picking position is (in this case our gripper closed fingertips is at 17.5 cm from End effector of UR5e)
 
-.. image:: images/html/TCPOffset.png
+.. image:: ../../../images/html/TCPOffset.png
     :alt: UR External Control
 
 

robotics-ai-suite/robot-vision-control/docs/source/use_cases/dynamic_use_case/system_config.rst → robotics-ai-suite/docs/rvc/use_cases/dynamic_use_case/system_config.rst

@@ -119,7 +119,7 @@ Configure the URCaps for the robot and the Robotiq 2F-85 URCap. For details, ref
 
 After installing `external_control.urcap`, the screen, shown in the following figure, will be displayed.
 
-.. image:: images/html/URExternalControl.png
+.. image:: ../../../images/html/URExternalControl.png
     :alt: UR External Control
 
 .. note::
@@ -142,7 +142,7 @@ Install these URCaps on the UR5e robot teach pendant using a USB drive.
 
 Restart the robot. Select **Program Robot** on the Welcome screen. Go to the **Installation** tab. Select **Gripper** listed under **URCaps**.
 
-.. image:: images/html/URRobotiqGripper.png
+.. image:: ../../../images/html/URRobotiqGripper.png
     :alt: UR Robotiq Gripper urcap
 
 
@@ -199,7 +199,7 @@ Create Program
 
 To use the new URCaps, enabling the communication with the Intel® architecture RVC controller, create a new program on the teaching pendant and insert the **External Control** program node in the program tree.
 
-.. image:: images/html//URCreateProgram.png
+.. image:: ../../../images/html//URCreateProgram.png
     :alt: Create Program
 
 .. note::
@@ -237,5 +237,5 @@ correctly homed before initiating any automated behavior.
 | Wrist 3  | 0°            |
 +----------+---------------+
 
-.. image:: images/html/sethomeposition.png
+.. image:: ../../../images/html/sethomeposition.png
    :alt: setting home position

robotics-ai-suite/robot-vision-control/docs/source/use_cases/dynamic_use_case/vision_main_node.rst → robotics-ai-suite/docs/rvc/use_cases/dynamic_use_case/vision_main_node.rst

@@ -49,18 +49,18 @@ Here the step by step procedure:
 - Create the stl file to 3D print the object via `FreeCAD <https://www.freecad.org/>`_ or similar
 - Import the stl file via `Blender <https://www.blender.org/>`_
 
-.. image:: images/html/importSTL.png
+.. image:: ../../../images/html/importSTL.png
    :alt: Import STL Blender menu
 
 
 - Edit so the metrics matches the Realsense Camera metrics: Units are in meters AND the center of the object is in the origin of blender and parallel to the axes where applicable. In short, perform scaling, rotating and translating operations so that dimension matches the realsense camera and the rototranslation from blender origin matches the desired outcome. For example, looking at the following image, the imported STL has been scaled down so the side of the cube is 5CM (0.05 meters), and translated down the Z axis of 0.025 centimeters, so the center of the cube is at 0,0,0. No rotation was needed as the cube was already parallel to the absolute reference system.
 
-.. image:: images/html/editObject.png
+.. image:: ../../../images/html/editObject.png
    :alt: Transform object by scaling, rotating and translating with Blender
 
 - Export the object in WaveFront format (.obj) as shown in picture
 
-.. image:: images/html/exportToObj.png
+.. image:: ../../../images/html/exportToObj.png
    :alt: Blender menu to export selected object to WaveFront format
 
 
@@ -69,7 +69,7 @@ Here the step by step procedure:
 Note: Important consideration: The RVC Pose Detector will align this object PCD file to the input cloud from realsense. This means calculating how much every points of the object pcd are translated and rotated on top of the realsense poincloud from the original file location. To have a consistent meaning, the object baricenter should be in the origin to simulate the center of the optical camera (where all the optical and depth information are translated to). in this way, the algorithm will determine how far and how rotated is the object from the camera optical lense. if the object is not centered in 0,0,0, this calculation would be wrong. See following picture:
 
 
-.. image:: images/html/CenteredObject.png
+.. image:: ../../../images/html/CenteredObject.png
    :alt: Vertices of a 0,0,0 centered object
 
 
@@ -91,7 +91,7 @@ Verify that the PCD file has enough points using the pcl_viewer tool which comes
 As show in following image  
 
 
-.. image:: images/html/pcl_viewer.png
+.. image:: ../../../images/html/pcl_viewer.png
    :alt: PCD visualizer
 
 rvc_use_case_binaries package creation

robotics-ai-suite/robot-vision-control/docs/source/use_cases/dynamic_use_case/visualization.rst → robotics-ai-suite/docs/rvc/use_cases/dynamic_use_case/visualization.rst

@@ -7,7 +7,7 @@ Rviz2 Plugin
 
 A rviz2 plugin has been implemented to give full control of the use case in the same HMI:
 
-.. image:: images/html/RvizDynamicUseCase1.png
+.. image:: ../../../images/html/RvizDynamicUseCase1.png
    :alt: RViz2 Control Panel Custom plugin
 
 - Enable/Disable motion button 

robotics-ai-suite/robot-vision-control/docs/source/use_cases/static_use_case.rst → robotics-ai-suite/docs/rvc/use_cases/static_use_case.rst

@@ -23,7 +23,7 @@ and orientation in space with a 2.5D algorithm and the robot picks it up accordi
 
 The only configuration needed on the robot, is to put the teaching pendant in ``remote control`` as show in following picture
 
-    .. image:: images/html/setremotecontrol.png
+    .. image:: ../../images/html/setremotecontrol.png
      :alt: Setting pendant to Remote control
 
 

robotics-ai-suite/robot-vision-control/docs/README.md

@@ -1,78 +1,3 @@
 # Robotic Vision & Control [RVC] Documentation
 
-This directory contains the **Robotic Vision & Control [RVC]** system documentation, which is built from source using [Sphinx](https://www.sphinx-doc.org/). The following instructions will guide you through setting up the environment, installing dependencies, and building the HTML documentation.
-
----
-
-## 1. Install System Dependencies
-
-Before setting up the Python environment, ensure that essential system packages are installed. These packages include:
-
-* `python3-pip` – for installing Python packages
-* `graphviz` – for rendering diagrams in Sphinx
-* `libenchant-2-dev` – required by spelling check extensions
-
-
-```bash
-sudo apt update
-sudo apt install python3-pip
-sudo apt install graphviz libenchant-2-dev
-```
-
----
-
-## 2. Set Up a Python Virtual Environment
-
-Though not necessary, it is recommended to use a virtual environment to keep dependencies isolated.
-
-```bash
-# Navigate to the documentation folder
-export DOCS_DIR=<path to edge-ai-suites folder>
-cd $DOCS_DIR/edge-ai-suites/robotics-ai-suite/robot-vision-control/docs
-
-# Create a new virtual environment
-python3 -m venv venv_robotics-ai-suite-docs
-
-# Activate the virtual environment
-source venv_robotics-ai-suite-docs/bin/activate
-```
-
----
-
-## 3. Upgrade pip, setuptools, and wheel
-
-Inside the virtual environment, upgrade core Python packaging tools. This ensures compatibility with modern packages.
-
-```bash
-pip install --upgrade pip setuptools wheel
-```
-
----
-
-## 4. Install Python Dependencies
-
-With the virtual environment active, install all Python dependencies required to build the documentation:
-
-```bash
-pip install -r requirements.txt
-```
-
-Now reactivate the virtual environment:
-
-```bash
-source venv_robotics-ai-suite-docs/bin/activate
-```
-
----
-
-## 5. Build HTML Documentation
-
-Once dependencies are installed and the virtual environment is active, generate the HTML version of the documentation:
-
-```bash
-make html
-```
-
-The output will be available in the `build/html` folder inside your `docs` directory. You can open the `index.html` file in a browser to view the documentation.
-
----
+The documentation files are at https://github.com/open-edge-platform/edge-ai-suites/tree/main/robotics-ai-suite/docs/rvc.