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TF2: Managing Your Transformations in ROS2

For 2024Fall EE211 Course Project

Last Update: 2024-11-13


What is TF2?

TF2 is a package in ROS2 that lets the user keep track of multiple coordinate frames over time. It maintains the relationship between coordinate frames in a tree structure buffered in time, and lets the user query for the transformation between any two frames at any point in time.

“In our project, you can obtain the transformation between the target grasping object and the end-effector_link of the PX100 arm utilizing TF2. Then execute the result of the inverse kinematics to move the arm to the target pose to grasp the object.”


An Example


0. Install TF2

sudo apt-get install ros-humble-tf2-ros
sudo apt-get install ros-humble-tf2
sudo apt-get install ros-humble-tf2-tools


1. Connect to your robot, then run ros2 launch interbotix_xsarm_descriptions xsarm_description.launch.py robot_model:=px100 use_joint_pub_gui:=true

After this, the tf2 tree will be built.

  • run ros2 run tf2_tools view_frames to visualize the tf2 tree, check the generated .pdf file.

  • run ros2 topic list, you can find the topic /tf and /tf_static are published.

  • run ros2 topic echo /tf to see the transformation information.


2. Create a listener node to get the transformation between two frames

Here is a one provided for you, which listens to the transformation between the base_link and ee_gripper_link of the PX100 arm.

import rclpy
from rclpy.node import Node
from tf2_ros import TransformException
from tf2_ros.buffer import Buffer
from tf2_ros.transform_listener import TransformListener

class FrameListener(Node):

    def __init__(self):
        super().__init__('tf2_frame_listener')

        # Declare and acquire `target_frame` and `source_frame` parameter
        self.base_frame = self.declare_parameter('arm_base_frame', 'px100/base_link').get_parameter_value().string_value
        self.ee_frame = self.declare_parameter('arm_ee_frame', 'px100/ee_gripper_link').get_parameter_value().string_value

        self.tf_buffer = Buffer()
        self.tf_listener = TransformListener(self.tf_buffer, self)
        
        # Call on_timer function every second
        self.timer = self.create_timer(1.0, self.on_timer)

    def on_timer(self):
        t = self.tf_buffer.lookup_transform(
                self.base_frame,
                self.ee_frame,
                rclpy.time.Time())
        self.get_logger().info('translation: {} \nrotation: {}'.format(t.transform.translation, t.transform.rotation))

def main():
    rclpy.init()
    node = FrameListener()
    try:
        rclpy.spin(node)
    except KeyboardInterrupt:
        pass

    rclpy.shutdown()

if __name__ == "__main__":
    main()

Keep the shell that runs ros2 launch interbotix_xsarm_descriptions xsarm_description.launch.py robot_model:=px100 use_joint_pub_gui:=true, you can run the python script directly to see the results (Integrate the script into a package in your seperate ros2 colcon workspace is more recommended).



Reference