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Writing a static broadcaster (Python)
Goal: Learn how to broadcast static coordinate frames to tf2.
Tutorial level: Intermediate
Time: 15 minutes
Contents
Background
Publishing static transforms is useful to define the relationship between a robot base and its sensors or non-moving parts. For example, it is easiest to reason about laser scan measurements in a frame at the center of the laser scanner.
This is a standalone tutorial covering the basics of static transforms, which consists of two parts.
In the first part we will write code to publish static transforms to tf2.
In the second part we will explain how to use the commandline static_transform_publisher
executable tool in tf2_ros
.
In the next two tutorials we will write the code to reproduce the demo from the Introduction to tf2 tutorial. After that, the following tutorials focus on extending the demo with more advanced tf2 features.
Prerequisites
In previous tutorials, you learned how to create a workspace and create a package.
Tasks
1 Create a package
First we will create a package that will be used for this tutorial and the following ones.
The package called learning_tf2_py
will depend on geometry_msgs
, python3-numpy
, rclpy
, tf2_ros_py
, and turtlesim
.
Code for this tutorial is stored here.
Open a new terminal and source your ROS 2 installation so that ros2
commands will work.
Navigate to workspace’s src
folder and create a new package:
ros2 pkg create --build-type ament_python learning_tf2_py
Your terminal will return a message verifying the creation of your package learning_tf2_py
and all its necessary files and folders.
2 Write the static broadcaster node
Let’s first create the source files.
Inside the src/learning_tf2_py/learning_tf2_py
directory download the example static broadcaster code by entering the following command:
wget https://raw.githubusercontent.com/ros/geometry_tutorials/ros2/turtle_tf2_py/turtle_tf2_py/static_turtle_tf2_broadcaster.py
wget https://raw.githubusercontent.com/ros/geometry_tutorials/ros2/turtle_tf2_py/turtle_tf2_py/static_turtle_tf2_broadcaster.py
In a Windows command line prompt:
curl -sk https://raw.githubusercontent.com/ros/geometry_tutorials/ros2/turtle_tf2_py/turtle_tf2_py/static_turtle_tf2_broadcaster.py -o static_turtle_tf2_broadcaster.py
Or in powershell:
curl https://raw.githubusercontent.com/ros/geometry_tutorials/ros2/turtle_tf2_py/turtle_tf2_py/static_turtle_tf2_broadcaster.py -o static_turtle_tf2_broadcaster.py
Open the file using your preferred text editor.
import math
import sys
from geometry_msgs.msg import TransformStamped
import numpy as np
import rclpy
from rclpy.node import Node
from tf2_ros.static_transform_broadcaster import StaticTransformBroadcaster
def quaternion_from_euler(ai, aj, ak):
ai /= 2.0
aj /= 2.0
ak /= 2.0
ci = math.cos(ai)
si = math.sin(ai)
cj = math.cos(aj)
sj = math.sin(aj)
ck = math.cos(ak)
sk = math.sin(ak)
cc = ci*ck
cs = ci*sk
sc = si*ck
ss = si*sk
q = np.empty((4, ))
q[0] = cj*sc - sj*cs
q[1] = cj*ss + sj*cc
q[2] = cj*cs - sj*sc
q[3] = cj*cc + sj*ss
return q
class StaticFramePublisher(Node):
"""
Broadcast transforms that never change.
This example publishes transforms from `world` to a static turtle frame.
The transforms are only published once at startup, and are constant for all
time.
"""
def __init__(self, transformation):
super().__init__('static_turtle_tf2_broadcaster')
self.tf_static_broadcaster = StaticTransformBroadcaster(self)
# Publish static transforms once at startup
self.make_transforms(transformation)
def make_transforms(self, transformation):
t = TransformStamped()
t.header.stamp = self.get_clock().now().to_msg()
t.header.frame_id = 'world'
t.child_frame_id = transformation[1]
t.transform.translation.x = float(transformation[2])
t.transform.translation.y = float(transformation[3])
t.transform.translation.z = float(transformation[4])
quat = quaternion_from_euler(
float(transformation[5]), float(transformation[6]), float(transformation[7]))
t.transform.rotation.x = quat[0]
t.transform.rotation.y = quat[1]
t.transform.rotation.z = quat[2]
t.transform.rotation.w = quat[3]
self.tf_static_broadcaster.sendTransform(t)
def main():
logger = rclpy.logging.get_logger('logger')
# obtain parameters from command line arguments
if len(sys.argv) != 8:
logger.info('Invalid number of parameters. Usage: \n'
'$ ros2 run learning_tf2_py static_turtle_tf2_broadcaster'
'child_frame_name x y z roll pitch yaw')
sys.exit(1)
if sys.argv[1] == 'world':
logger.info('Your static turtle name cannot be "world"')
sys.exit(2)
# pass parameters and initialize node
rclpy.init()
node = StaticFramePublisher(sys.argv)
try:
rclpy.spin(node)
except KeyboardInterrupt:
pass
rclpy.shutdown()
2.1 Examine the code
Now let’s look at the code that is relevant to publishing the static turtle pose to tf2.
The first lines import required packages.
First we import the TransformStamped
from the geometry_msgs
, which provides us a template for the message that we will publish to the transformation tree.
from geometry_msgs.msg import TransformStamped
Afterward, rclpy
is imported so its Node
class can be used.
import rclpy
from rclpy.node import Node
The tf2_ros
package provides a StaticTransformBroadcaster
to make the publishing of static transforms easy.
To use the StaticTransformBroadcaster
, we need to import it from the tf2_ros
module.
from tf2_ros.static_transform_broadcaster import StaticTransformBroadcaster
The StaticFramePublisher
class constructor initializes the node with the name static_turtle_tf2_broadcaster
.
Then, StaticTransformBroadcaster
is created, which will send one static transformation upon the startup.
self.tf_static_broadcaster = StaticTransformBroadcaster(self)
self.make_transforms(transformation)
Here we create a TransformStamped
object, which will be the message we will send over once populated.
Before passing the actual transform values we need to give it the appropriate metadata.
We need to give the transform being published a timestamp and we’ll just stamp it with the current time,
self.get_clock().now()
Then we need to set the name of the parent frame of the link we’re creating, in this case
world
Finally, we need to set the name of the child frame of the link we’re creating
t = TransformStamped()
t.header.stamp = self.get_clock().now().to_msg()
t.header.frame_id = 'world'
t.child_frame_id = transformation[1]
Here we populate the 6D pose (translation and rotation) of the turtle.
t.transform.translation.x = float(transformation[2])
t.transform.translation.y = float(transformation[3])
t.transform.translation.z = float(transformation[4])
quat = quaternion_from_euler(
float(transformation[5]), float(transformation[6]), float(transformation[7]))
t.transform.rotation.x = quat[0]
t.transform.rotation.y = quat[1]
t.transform.rotation.z = quat[2]
t.transform.rotation.w = quat[3]
Finally, we broadcast static transform using the sendTransform()
function.
self.tf_static_broadcaster.sendTransform(t)
2.2 Add dependencies
Navigate one level back to the src/learning_tf2_py
directory, where the setup.py
, setup.cfg
, and package.xml
files have been created for you.
Open package.xml
with your text editor.
As mentioned in the Create a package tutorial, make sure to fill in the <description>
, <maintainer>
and <license>
tags:
<description>Learning tf2 with rclpy</description>
<maintainer email="you@email.com">Your Name</maintainer>
<license>Apache License 2.0</license>
After the lines above, add the following dependencies corresponding to your node’s import statements:
<exec_depend>geometry_msgs</exec_depend>
<exec_depend>python3-numpy</exec_depend>
<exec_depend>rclpy</exec_depend>
<exec_depend>tf2_ros_py</exec_depend>
<exec_depend>turtlesim</exec_depend>
This declares the required geometry_msgs
, python3-numpy
, rclpy
, tf2_ros_py
, and turtlesim
dependencies when its code is executed.
Make sure to save the file.
2.3 Add an entry point
To allow the ros2 run
command to run your node, you must add the entry point to setup.py
(located in the src/learning_tf2_py
directory).
Add the following line between the 'console_scripts':
brackets:
'static_turtle_tf2_broadcaster = learning_tf2_py.static_turtle_tf2_broadcaster:main',
3 Build
It’s good practice to run rosdep
in the root of your workspace to check for missing dependencies before building:
rosdep install -i --from-path src --rosdistro rolling -y
rosdep only runs on Linux, so you will need to install geometry_msgs
and turtlesim
dependencies yourself
rosdep only runs on Linux, so you will need to install geometry_msgs
and turtlesim
dependencies yourself
Still in the root of your workspace, build your new package:
colcon build --packages-select learning_tf2_py
colcon build --packages-select learning_tf2_py
colcon build --merge-install --packages-select learning_tf2_py
Open a new terminal, navigate to the root of your workspace, and source the setup files:
. install/setup.bash
. install/setup.bash
# CMD
call install\setup.bat
# Powershell
.\install\setup.ps1
4 Run
Now run the static_turtle_tf2_broadcaster
node:
ros2 run learning_tf2_py static_turtle_tf2_broadcaster mystaticturtle 0 0 1 0 0 0
This sets a turtle pose broadcast for mystaticturtle
to float 1 meter above the ground.
We can now check that the static transform has been published by echoing the tf_static
topic
ros2 topic echo /tf_static
If everything went well you should see a single static transform
transforms:
- header:
stamp:
sec: 1622908754
nanosec: 208515730
frame_id: world
child_frame_id: mystaticturtle
transform:
translation:
x: 0.0
y: 0.0
z: 1.0
rotation:
x: 0.0
y: 0.0
z: 0.0
w: 1.0
The proper way to publish static transforms
This tutorial aimed to show how StaticTransformBroadcaster
can be used to publish static transforms.
In your real development process you shouldn’t have to write this code yourself and should use the dedicated tf2_ros
tool to do so.
tf2_ros
provides an executable named static_transform_publisher
that can be used either as a commandline tool or a node that you can add to your launchfiles.
Publish a static coordinate transform to tf2 using an x/y/z offset in meters and roll/pitch/yaw in radians. In our case, roll/pitch/yaw refers to rotation about the x/y/z-axis, respectively.
ros2 run tf2_ros static_transform_publisher --x x --y y --z z --yaw yaw --pitch pitch --roll roll --frame-id frame_id --child-frame-id child_frame_id
Publish a static coordinate transform to tf2 using an x/y/z offset in meters and quaternion.
ros2 run tf2_ros static_transform_publisher --x x --y y --z z --qx qx --qy qy --qz qz --qw qw --frame-id frame_id --child-frame-id child_frame_id
static_transform_publisher
is designed both as a command-line tool for manual use, as well as for use within launch
files for setting static transforms. For example:
from launch import LaunchDescription
from launch_ros.actions import Node
def generate_launch_description():
return LaunchDescription([
Node(
package='tf2_ros',
executable='static_transform_publisher',
arguments = ['--x', '0', '--y', '0', '--z', '1', '--yaw', '0', '--pitch', '0', '--roll', '0', '--frame-id', 'world', '--child-frame-id', 'mystaticturtle']
),
])
Note that all arguments except for --frame-id
and --child-frame-id
are optional; if a particular option isn’t specified, then the identity will be assumed.
Summary
In this tutorial you learned how static transforms are useful to define static relationships between frames, like mystaticturtle
in relation to the world
frame.
In addition, you learned how static transforms can be useful for understanding sensor data, such as from laser scanners, by relating the data to a common coordinate frame.
Finally, you wrote your own node to publish static transforms to tf2 and learned how to publish required static transformations using static_transform_publisher
executable and launch files.