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[Documentation] Update ros1 and ros2 model description
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‎README.md‎

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- [(Only for tooling developers) From Source code in eclipse](docu/Installation.md#option-2-using-the-eclipse-installer---source-installation-ros-tooling-developers)
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- VS Code plugin(tbd) - WIP [vscode-RosTooling](https://github.com/ipa320/vscode-RosTooling)
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## Tutorials
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## Tutorials v3
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- Create component models:
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- (Prerequisite) [Add communication objects](docu/NewCommunicationObjects.md)
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- [Create a ROS model from your source code(static code analyzer)](docu/NewRosModel.md)
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- [Create manually a new ROS component description](docu/RosModelDescription.md)
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- [Generation of code from models](https://github.com/CoreSenseEU/rossdl#usage)
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- [Create a ROS model from a deployed robot using our introspection at runtime tool](docu/IntrospectionNode.md)
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- [Create new ROS component description](docu/RosModelDescription.md)
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- [Generation of code from models](docu/CodeGeneration.md)
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- [Create a ROS model from your source code(static code analyzer)](docu/NewRosModel.md))
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- Combine components to form a ROS System
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- [Create manually a new RosSystem description](docu/RosSystemModelDescription.md)

‎docu/IntrospectionNode.md‎

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## Create a ROS model from a deployed robot using our introspection at runtime tool
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## Create a ROS model from a deployed robot using our introspection at runtime tool (for ROS 2 systems)
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Please be sure that the tool is installed and your workspace setup, see the [installation guide](../README.md) for further details.
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You can install the tools directly on your workspace using the following command:
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```
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mkdir -p my_catkin_ws/src
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cd my_catkin_ws/src
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catkin_init_workspace
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rosinstall . https://raw.githubusercontent.com/ipa320/ros-model/master/docu/introspection.rosinstall
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cd my_catkin_ws
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catkin_make (or catkin build)
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cd YourRos2WS/src
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git clone git@github.com:ipa-nhg/ros2model.git
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cd YourRos2WS
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colcon build
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```
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To start the monitoring software the snapshot node has to be started on the same machine where the software to be analysed is running:
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To ask the monitoring module to capture all the nodes running on the system, please use the following command:
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```
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source my_catkin_ws/devel/setup.bash
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rosrun rosgraph_monitor rossystem_snapshot
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ros2 model running_node -ga -d ~/PathToModelsFolderOutput
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```
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This script will generate automatically a new file (.rossystem) under the folder: 'rosgraph_monitor/results'.
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The folder **PathToModelsFolderOutput** will contain all the model files.
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For a single node, the following command can be called:
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```
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ros2 model running_node [-o Outputfile] <node-name>
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```
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For further information please check the [ros2model](https://github.com/ipa-cmh/ros2model) repository.

‎docu/NewRosModel.md‎

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:bangbang::bangbang::bangbang::bangbang: This tutorial is only working for previous versions of the RosTooling (v2)
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## Create a ROS model from your code
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Please be sure that the tool is installed and your workspace setup, see the [installation guide](../README.md) for further details.
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To extract your model from ROS code ou have 3 options:
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- [Use the available web interface to autogenerate models from code hosted on GitHub](#cloud)
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To extract your model from ROS code ou have 2 options:
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- [Call our docker container configuration for the extraction from a GitHub hosted repository (requires only the installation of Docker)](#docker-container)
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- [Use a local build of your ROS package (requires the local installation of HAROS)](#local-ros-workspace)
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### Cloud
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Under the link [Model extractor](http://ros-model.seronet-project.de/) a web service to extract automatically models from existing open source ROS packages is available. The user only has to give as input the URL address of the repository (for example https://github.com/ipa320/cob_driver), the name of the package that contains the node to be analysed (for example cob_sick_s300) and the name of th node ( for example cob_sick_s300). The resulted model will be displayed on the right side of the window.
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![alt text](images/cob_sick_s300_cloud.png)
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### Docker container
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Clone the repository [ros-model-extractors](https://github.com/ipa320/ros-model-extractors) and follow its [documentation instructions](https://github.com/ipa320/ros-model-extractors#ros-model-extractors).

‎docu/RosModelDescription.md‎

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## TBD
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# HOW TO DESCRIBE ROS NODES USING THE LANGUAGE
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Component models have two types of extensions, either .ros1 for ROS version 1 packages and .ros2 for ROS 2 packages. In both cases the language allows to describe ros nodes and their interfaces.
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To create a new model, you can easily just create a new file with the correct extension.
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The textual editor contains checker embedded, for example:
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![alt text](images/RosModelEmbededChecker.gif)
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It incorporates also the auto-complete function. This is available by pressing **Ctrl** + the space bar:
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![alt text](images/RosModelAutocomplete.gif)
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## ROS (1)
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In ros1 the grammar is as follows:
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```
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my_awesome_pkg:
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**fromGitRepo: ** "http://github.com/MyAccount/RepoName:BranchName"
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**artifacts:**
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awesome:
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**node:** awesome_node
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**publishers:**
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awesome_pub:
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**type:** "std_msgs/msg/Bool"
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**subscribers:**
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awesome_sub:
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**type:** "std_msgs/msg/Bool"
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**serviceclients:**
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awesome_client:
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**type:** "std_srvs/srv/Empty"
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**serviceservers:**
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awesome_server:
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**type:** "std_srvs/srv/Empty"
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**actionclients:**
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awesome_action:
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**type:** "control_msgs/action/JointTrajectory"
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**actionservers:**
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awesome_action:
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**type:** "control_msgs/action/JointTrajectory"
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**parameters:**
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awesome_param:
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**type:** String
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**default:** "Hello"
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```
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For the known teleop ROS package the models looks like:
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```
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teleop:
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artifacts:
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teleop_twist_joy_node:
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node: teleop_twist_joy_node
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publishers:
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cmd_vel:
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type: "geometry_msgs/msg/Twist"
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subscribers:
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joy:
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type:"sensor_msgs/msg/Joy"
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```
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## ROS 2
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The ros2 grammar is as follows:
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```
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my_awesome_pkg:
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**fromGitRepo: ** "http://github.com/MyAccount/RepoName:BranchName"
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**artifacts:**
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awesome:
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**node:** awesome_node
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**publishers:**
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awesome_pub:
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**type:** "std_msgs/msg/Bool"
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**qos:**
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**depth:** 10
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**durability:** volatile
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**history:** keep_all
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**profile:** default_qos
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**reliability:** best_effort
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**subscribers:**
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awesome_sub:
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**type:** "std_msgs/msg/Bool"
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**qos:**
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**depth:** 10
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**durability:** transient_local
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**history:** keep_last
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**profile:** sensor_qos
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**reliability:** reliable
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**serviceclients:**
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awesome_client:
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**type:** "std_srvs/srv/Empty"
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**qos:**
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**depth:** 10
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**durability:** volatile
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**history:** keep_all
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**profile:** services_qos
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**reliability:** best_effort
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**serviceservers:**
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awesome_server:
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**type:** "std_srvs/srv/Empty"
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**qos:**
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**depth:** 10
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**durability:** volatile
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**history:** keep_all
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**profile:** services_qos
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**reliability:** best_effort
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**actionclients:**
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awesome_action:
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**type:** "control_msgs/action/JointTrajectory"
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**qos:**
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**depth:** 10
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**durability:** volatile
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**history:** keep_all
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**profile:** default_qos
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**reliability:** best_effort
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**actionservers:**
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awesome_action:
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**type:** "control_msgs/action/JointTrajectory"
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**qos:**
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**depth:** 10
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**durability:** volatile
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**history:** keep_all
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**profile:** default_qos
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**reliability:** best_effort
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**parameters:**
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awesome_param:
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**type:** String
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**default:** "Hello"
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**qos:**
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**depth:** 10
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**durability:** volatile
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**history:** keep_all
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**profile:** parameter_qos
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**reliability:** best_effort
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```
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The only remarkable difference with the ROS 1 model is that the quality of service can be defined for all the different interfaces. The quality of service atrributes are optional and they allow the following options:
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- depth : it must be an integer.
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- durability: volatile / transient_local
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- history: keep_all / keep_last
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- profile: default_qos / sensor_qos / services_qos/ parameter_qos
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- reliability: best_effort / reliable
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See the following example for the [arucos_ros](https://github.com/pal-robotics/aruco_ros) driver:
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```
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aruco_ros:
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fromGitRepo: "https://github.com/pal-robotics/aruco_ros.git:humble-devel"
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artifacts:
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marker_publisher:
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node: marker_publisher
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subscribers:
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image_raw:
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type: "sensor_msgs/msg/Image"
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publishers:
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debug:
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type: "sensor_msgs/msg/Image"
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markers:
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type: "aruco_msgs/msg/MarkerArray"
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markers_list:
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type: "std_msgs/msg/UInt32MultiArray"
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result:
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type: "sensor_msgs/msg/Image"
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parameters:
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camera_frame:
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type: String
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image_is_rectified:
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type: Boolean
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marker_size:
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type: Double
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reference_frame:
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type: String
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raw_image_topic:
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type: String
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use_camera_info:
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type: Boolean
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use_sim_time:
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type: Boolean
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camera_info_topic:
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type: String
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```

‎docu/images/RosModelAutocomplete.gif‎

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‎docu/images/RosModelEmbededChecker.gif‎

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