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Restructure documentation for full stack documentation (#984)
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* Remove indices and tables from the ur_robot_driver index
* Move ur_controllers documentation to doc folder
* Move ur_calibration documentation to rst so it can be re-used
* Rework calibration tutorial to refer to the workcell example
* Migrate all docs to rst
* Add rst doc for ur_moveit_config

Co-authored-by: Vincenzo Di Pentima <[email protected]>
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fmauch and VinDp authored May 17, 2024
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69 changes: 1 addition & 68 deletions ur_calibration/README.md
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Expand Up @@ -8,71 +8,4 @@ make use of this in ROS, you first have to extract the calibration information f
Though this step is not necessary, to control the robot using this driver, it is highly recommended
to do so, as end effector positions might be off in the magnitude of centimeters.

## Nodes
### calibration_correction
This node extracts calibration information directly from a robot, calculates the URDF correction and
saves it into a .yaml file.

In the launch folder of the ur_calibration package is a helper script:

```bash
$ ros2 launch ur_calibration calibration_correction.launch.py \
robot_ip:=<robot_ip> target_filename:="${HOME}/my_robot_calibration.yaml"
```

For the parameter `robot_ip` insert the IP address on which the ROS pc can reach the robot. As
`target_filename` provide an absolute path where the result will be saved to.

## Creating a calibration / launch package for all local robots
When dealing with multiple robots in one organization it might make sense to store calibration data
into a package dedicated to that purpose only. To do so, create a new package (if it doesn't already
exist)

```bash
# Replace your actual colcon_ws folder
$ cd <colcon_ws>/src
$ ros2 pkg create <organization_name>_ur_launch --build-type ament_cmake --dependencies ur_client_library \
--description "Package containing calibrations and launch files for our UR robots."
# Create a skeleton package
$ mkdir -p <organization_name>_ur_launch/etc
$ mkdir -p <organization_name>_ur_launch/launch
$ echo 'install(DIRECTORY etc launch DESTINATION share/${PROJECT_NAME})' >> <organization_name>_ur_launch/CMakeLists.txt
$ colcon build --packages-select <organization_name>_ur_launch
```

We can use the new package to store the calibration data in that package. We recommend naming each
robot individually, e.g. *ex-ur10-1*.

```bash
$ ros2 launch ur_calibration calibration_correction.launch.py \
robot_ip:=<robot_ip> \
target_filename:="$(ros2 pkg prefix <organization_name>_ur_launch)/share/<organization_name>_ur_launch/etc/ex-ur10-1_calibration.yaml"
```

To make life easier, we create a launchfile for this particular robot. We base it upon the
respective launchfile in the driver:

```bash
# Replace your actual colcon_ws folder
$ cd <colcon_ws>/src/<organization_name>_ur_launch/launch
$ cp $(ros2 pkg prefix ur_robot_driver)/share/ur_robot_driver/launch/ur_control.launch.py ex-ur10-1.launch.py
```

Next, modify the parameter section of the new launchfile to match your actual calibration:

```py
kinematics_params = PathJoinSubstitution(
[FindPackageShare("<organization_name>_ur_launch"), "etc", "", "ex-ur10-1_calibration.yaml"]
)

```

Then, anybody cloning this repository can startup the robot simply by launching

```bash
# Replace your actual colcon_ws folder
$ cd <colcon_ws>
$ colcon build --packages-select <organization_name>_ur_launch
$ ros2 launch <organization_name>_ur_launch ex-ur10-1.launch.py
robot_ip:=xxx.yyy.zzz.www ur_type:=ur5e use_mock_hardware:=false launch_rviz:=true
```
For details please see [doc/index.rst](doc/index.rst)
45 changes: 45 additions & 0 deletions ur_calibration/doc/index.rst
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ur_calibration
==============

Package for extracting the factory calibration from a UR robot and changing it to be used by ``ur_description`` to gain a correct URDF model.

Each UR robot is calibrated inside the factory giving exact forward and inverse kinematics. To also
make use of this in ROS, you first have to extract the calibration information from the robot.

Though this step is not necessary, to control the robot using this driver, it is highly recommended
to do so, as end effector positions might be off in the magnitude of centimeters.

Nodes
-----

calibration_correction
^^^^^^^^^^^^^^^^^^^^^^

This node extracts calibration information directly from a robot, calculates the URDF correction and
saves it into a .yaml file.

In the launch folder of the ur_calibration package is a helper script:

.. code-block:: bash
$ ros2 launch ur_calibration calibration_correction.launch.py \
robot_ip:=<robot_ip> target_filename:="${HOME}/my_robot_calibration.yaml"
For the parameter ``robot_ip`` insert the IP address on which the ROS pc can reach the robot. As
``target_filename`` provide an absolute path where the result will be saved to.

With that, you can launch your specific robot with the correct calibration using

.. code-block:: bash
$ ros2 launch ur_robot_driver ur_control.launch.py \
ur_type:=ur5e \
robot_ip:=192.168.56.101 \
kinematics_params_file:="${HOME}/my_robot_calibration.yaml"
Adapt the robot model matching to your robot.

Ideally, you would create a package for your custom workcell, as explained in `the custom workcell
tutorial
<https://github.com/UniversalRobots/Universal_Robots_ROS2_Tutorials/blob/main/my_robot_cell/doc/start_ur_driver.rst#extract-the-calibration>`_.
64 changes: 1 addition & 63 deletions ur_controllers/README.md
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Expand Up @@ -11,66 +11,4 @@ robot family. Currently this contains
* A **scaled_joint_trajectory_controller** that is similar to the *joint_trajectory_controller*,
but it uses the speed scaling reported by the robot to reduce progress in the trajectory.

## About this package
This package contains controllers not being available in the default `ros_control` set. They are
created to support more features offered by the UR robot family. Any of these controllers are
example implementations for certain features and are intended to be generalized and merged
into the default `ros_control` controller set at some future point.

## Controller description
This packages offers a couple of specific controllers that will be explained in the following
sections.
### ur_controllers/SpeedScalingStateBroadcaster
This controller publishes the current actual execution speed as reported by the robot. Values are
floating points between 0 and 1.

In the [`ur_robot_driver`](../ur_robot_driver) this is calculated by multiplying the two [RTDE](https://www.universal-robots.com/articles/ur/real-time-data-exchange-rtde-guide/) data
fields `speed_scaling` (which should be equal to the value shown by the speed slider position on the
teach pendant) and `target_speed_fraction` (Which is the fraction to which execution gets slowed
down by the controller).
### position_controllers/ScaledJointTrajectoryController and velocity_controllers/ScaledJointTrajectoryController
These controllers work similar to the well-known
[`joint_trajectory_controller`](http://wiki.ros.org/joint_trajectory_controller).

However, they are extended to handle the robot's execution speed specifically. Because the default
`joint_trajectory_controller` would interpolate the trajectory with the configured time constraints (ie: always assume maximum velocity and acceleration supported by the robot),
this could lead to significant path deviation due to multiple reasons:
- The speed slider on the robot might not be at 100%, so motion commands sent from ROS would
effectively get scaled down resulting in a slower execution.
- The robot could scale down motions based on configured safety limits resulting in a slower motion
than expected and therefore not reaching the desired target in a control cycle.
- Motions might not be executed at all, e.g. because the robot is E-stopped or in a protective stop
- Motion commands sent to the robot might not be interpreted, e.g. because there is no
[`external_control`](https://github.com/UniversalRobots/Universal_Robots_ROS_Driver#prepare-the-robot)
program node running on the robot controller.
- The program interpreting motion commands could be paused.

The following plot illustrates the problem:
![Trajectory execution with default trajectory controller](doc/traj_without_speed_scaling.png
"Trajectory execution with default trajectory controller")

The graph shows a trajectory with one joint being moved to a target point and back to its starting
point. As the joint's speed is limited to a very low setting on the teach pendant, speed scaling
(black line) activates and limits the joint speed (green line). As a result, the target
trajectory (light blue) doesn't get executed by the robot, but instead the pink trajectory is executed.
The vertical distance between the light blue line and the pink line is the path error in each
control cycle. We can see that the path deviation gets above 300 degrees at some point and the
target point at -6 radians never gets reached.

All of the cases mentioned above are addressed by the scaled trajectory versions. Trajectory execution
can be transparently scaled down using the speed slider on the teach pendant without leading to
additional path deviations. Pausing the program or hitting the E-stop effectively leads to
`speed_scaling` being 0 meaning the trajectory will not be continued until the program is continued.
This way, trajectory executions can be explicitly paused and continued.

With the scaled version of the trajectory controller the example motion shown in the previous diagram becomes:
![Trajectory execution with scaled_joint_trajectory_controller](doc/traj_with_speed_scaling.png
"Trajectory execution with scaled_joint_trajectory_controller")

The deviation between trajectory interpolation on the ROS side and actual robot execution stays minimal and the
robot reaches the intermediate setpoint instead of returning "too early" as in the example above.

Under the hood this is implemented by proceeding the trajectory not by a full time step but only by
the fraction determined by the current speed scaling. If speed scaling is currently at 50% then
interpolation of the current control cycle will start half a time step after the beginning of the
previous control cycle.
For more details please see [doc/index.rst](doc/index.rst)
99 changes: 99 additions & 0 deletions ur_controllers/doc/index.rst
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ur_controllers
==============

This package contains controllers and hardware interface for ``ros_control`` that are special to the UR
robot family. Currently this contains:


* A **speed_scaling_interface** to read the value of the current speed scaling into controllers.
* A **scaled_joint_command_interface** that provides access to joint values and commands in
combination with the speed scaling value.
* A **speed_scaling_state_controller** that publishes the current execution speed as reported by
the robot to a topic interface. Values are floating points between 0 and 1.
* A **scaled_joint_trajectory_controller** that is similar to the *joint_trajectory_controller*\ ,
but it uses the speed scaling reported by the robot to reduce progress in the trajectory.

About this package
------------------

This package contains controllers not being available in the default ``ros_control`` set. They are
created to support more features offered by the UR robot family. Any of these controllers are
example implementations for certain features and are intended to be generalized and merged
into the default ``ros_control`` controller set at some future point.

Controller description
----------------------

This packages offers a couple of specific controllers that will be explained in the following
sections.

ur_controllers/SpeedScalingStateBroadcaster
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

This controller publishes the current actual execution speed as reported by the robot. Values are
floating points between 0 and 1.

In the `ur_robot_driver
<https://index.ros.org/p/ur_robot_driver/github-UniversalRobots-Universal_Robots_ROS2_Driver/>`_
this is calculated by multiplying the two `RTDE
<https://www.universal-robots.com/articles/ur/real-time-data-exchange-rtde-guide/>`_ data
fields ``speed_scaling`` (which should be equal to the value shown by the speed slider position on the
teach pendant) and ``target_speed_fraction`` (Which is the fraction to which execution gets slowed
down by the controller).

position_controllers/ScaledJointTrajectoryController and velocity_controllers/ScaledJointTrajectoryController
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

These controllers work similar to the well-known
`joint_trajectory_controller <https://control.ros.org/master/doc/ros2_controllers/joint_trajectory_controller/doc/userdoc.html>`_.

However, they are extended to handle the robot's execution speed specifically. Because the default
``joint_trajectory_controller`` would interpolate the trajectory with the configured time constraints (ie: always assume maximum velocity and acceleration supported by the robot),
this could lead to significant path deviation due to multiple reasons:


* The speed slider on the robot might not be at 100%, so motion commands sent from ROS would
effectively get scaled down resulting in a slower execution.
* The robot could scale down motions based on configured safety limits resulting in a slower motion
than expected and therefore not reaching the desired target in a control cycle.
* Motions might not be executed at all, e.g. because the robot is E-stopped or in a protective stop
* Motion commands sent to the robot might not be interpreted, e.g. because there is no
`external_control <https://github.com/UniversalRobots/Universal_Robots_ROS_Driver#prepare-the-robot>`_
program node running on the robot controller.
* The program interpreting motion commands could be paused.

The following plot illustrates the problem:

.. image:: traj_without_speed_scaling.png
:target: traj_without_speed_scaling.png
:alt: Trajectory execution with default trajectory controller


The graph shows a trajectory with one joint being moved to a target point and back to its starting
point. As the joint's speed is limited to a very low setting on the teach pendant, speed scaling
(black line) activates and limits the joint speed (green line). As a result, the target
trajectory (light blue) doesn't get executed by the robot, but instead the pink trajectory is executed.
The vertical distance between the light blue line and the pink line is the path error in each
control cycle. We can see that the path deviation gets above 300 degrees at some point and the
target point at -6 radians never gets reached.

All of the cases mentioned above are addressed by the scaled trajectory versions. Trajectory execution
can be transparently scaled down using the speed slider on the teach pendant without leading to
additional path deviations. Pausing the program or hitting the E-stop effectively leads to
``speed_scaling`` being 0 meaning the trajectory will not be continued until the program is continued.
This way, trajectory executions can be explicitly paused and continued.

With the scaled version of the trajectory controller the example motion shown in the previous diagram becomes:

.. image:: traj_with_speed_scaling.png
:target: traj_with_speed_scaling.png
:alt: Trajectory execution with scaled_joint_trajectory_controller


The deviation between trajectory interpolation on the ROS side and actual robot execution stays minimal and the
robot reaches the intermediate setpoint instead of returning "too early" as in the example above.

Under the hood this is implemented by proceeding the trajectory not by a full time step but only by
the fraction determined by the current speed scaling. If speed scaling is currently at 50% then
interpolation of the current control cycle will start half a time step after the beginning of the
previous control cycle.
25 changes: 25 additions & 0 deletions ur_moveit_config/doc/index.rst
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.. _ur_moveit_config:

================
ur_moveit_config
================

This package contains an **example** MoveIt! configuration for Universal Robots arms. Since the
default description contains only the arm, this MoveIt! configuration package also only contains the
arm without any objects around it.
In a real-world scenario it is recommended to create a robot_description modelling the robot with its surroundings (e.g. table where it is mounted on, objects in its environment, etc.) and to generate a
*scenario_moveit_config* package from that description as explained in the :ref:`Custom workcell
tutorial <custom_workcell_tutorial>`.

Usage
-----

With a running driver (real hardware, URSim or mocked hardware), simply start the MoveIt!
interaction using

.. code-block::
ros2 launch ur_moveit_config ur_moveit.launch.py ur_type:=ur5e launch_rviz:=true
Now you should be able to use the MoveIt Plugin in rviz2 to plan and execute trajectories with the
robot as explained `here <https://moveit.picknik.ai/main/doc/tutorials/quickstart_in_rviz/quickstart_in_rviz_tutorial.html>`_.
8 changes: 4 additions & 4 deletions ur_robot_driver/README.md
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Expand Up @@ -5,7 +5,7 @@ repository and requires other packages from that repository. Also, see the [main
README](../README.md) for information on how to install and startup this driver.

## ROS-API
The ROS API is documented in a [standalone document](doc/ROS_INTERFACE.md).
The ROS API is documented in a [standalone document](doc/ROS_INTERFACE.rst).

## Technical details
The following image shows a very coarse overview of the driver's architecture.
Expand Down Expand Up @@ -41,7 +41,7 @@ The robot won't accept script code from a remote source unless the robot is put
*remote_control-mode*. However, if put into *remote_control-mode*, the program containing the
**External Control** program node can't be started from the panel.
For this purpose, please use the **dashboard** services to load, start and stop the main program
running on the robot. See the [ROS-API documentation](doc/ROS_INTERFACE.md) for details on the
running on the robot. See the [ROS-API documentation](doc/ROS_INTERFACE.rst) for details on the
dashboard services.

For using the **tool communication interface** on e-Series robots, a `socat` script is prepared to
Expand Down Expand Up @@ -75,12 +75,12 @@ The **remote control mode** is needed for many aspects of this driver such as

### Headless mode
Inside this driver, there's the **headless** mode, which can be either enabled or not. When the
[headless mode](./doc/ROS_INTERFACE.md#headless_mode-default-false) is activated, required script
[headless mode](./doc/ROS_INTERFACE.rst#headless_mode-default-false) is activated, required script
code for external control will be sent to the robot directly when the driver starts. As soon as
other script code is sent to the robot either by sending it directly through this driver or by
pressing any motion-related button on the teach pendant, the script will be overwritten by this
action and has to be restarted by using the
[resend_robot_program](./doc/ROS_INTERFACE.md#resend_robot_program-std_srvstrigger) service. If this
[resend_robot_program](./doc/ROS_INTERFACE.rst#resend_robot_program-std_srvstrigger) service. If this
is necessary, you will see the output `Connection to robot dropped, waiting for new connection.`
from the driver. Note that pressing "play" on the TP won't start the external control again, but
whatever program is currently loaded on the controller. This mode doesn't require the "External
Expand Down
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