tf2_server repository

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Last Updated 2020-07-11
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Name Version
tf2_server 1.0.6




An upgraded tf2_ros/buffer_server. Main features are:

  • It supports the same action API as tf2_ros/buffer_server node for on-demand transform querying (which is however not suitable for fast queries).
  • It allows clients to request only subparts (or "streams") of the TF tree, which results in lowering the data transfer rates and computational burden of TF clients.
  • It provides C++ and Python helper libraries that make the subtree subscription easier. However, use of these libraries is optional and client code can make full use of subscription to a TF subtree just by correct configuration in .launch files.
  • It can be used as a TF concentrator which reduces the usual M:N connection nature of the TF topic to a M:1 and 1:N.

The subtree subscription mode is useful as a middle way between standard TransformListener and the action interface of the buffer_server - it transmits only the requested transform(s), but isn't burdened with the overhead the action interface brings in.

The server publishes the so called "TF streams", which are internally utilized by the helper libraries, but can also be used by custom user code. The streams can either be requested dynamically by calling service ~/request_transform_stream or by setting an initial set of streams using the streams parameter described in the following section.

Nodes and nodelets

This package provides node tf2_server_node and nodelet tf2_server/nodelet with equal functionality. Try running the nodelet version with your TF-hungry nodes.


  • tf2_msgs/LookupTransform: Depending on value of parameter ~use_node_namespace, this action is either published in namespace of the node, or in namespace tf2_buffer_server.


The first 3 parameters are taken from the original TF2 buffer server. To stay compatible, the parameters are not node-private, but should be set "one level" higher, e.g. besides the node and not inside it.

  • double buffer_size: Duration of the buffer memory (in seconds). Default is 120.0.
  • bool publish_frame_service: If True, the server will enable service ~/tf2_frames which shows debug information about the contents of the buffer. Default is False.
  • bool use_node_namespace: If True, the lookup transform action of this server will be published under the namespace of this tf2_server. If False, the action server will be published in namespace tf2_buffer_server. Default is False.

  • double ~transforms_update_period: The period at which the server looks for newly added TF frames.

  • double ~initial_streams_wait_time: Specifies how long to wait before registering streams from parameter streams (in seconds). This helps in case not all frames are right away available and you do not want to dynamically update the lists of available frames.

  • dict ~streams: If nonempty, specifies some TF streams that should be registered right after starting the server. Each stream has a name (its key in this dict). The stream will be published at ~/stream_key and ~/stream_key/static. The structure is the following and is described in more detail in the following section:

    parent_frame: 'base_link'
    child_frames: []
    intermediate_frames: True
    publication_period: 0.1
    publisher_queue_size: 11
    allow_transforms_update: True


  • tf2_server/RequestTransformStream ~/request_transform_stream: Requests a transform stream satisfying the given parameters.
  • tf2_msgs/FrameGraph ~/tf2_frames: Returns a list of all available frames seen by the buffer server.

tf2_server_node publications and subscriptions

  • /tf, /tf_static: The original TF topics.
  • ~/stream_key, ~/stream_key/static for each stream_key


The subtree subscription API is built around ReuqestTranformStream service type. The subtree listeners are configured by RequestTransformStreamRequest objects. The meaning of the individual fields is as follows:

  • string parent_frame: The top-most frame in TF tree you're interested in.
  • string[] child_frames: In case a nonempty list is given, this specifies the child transforms you are interested in. They don't need to be direct children of parent_frame, but they should be in the same TF tree. If an empty list is given, stream the whole subtree of parent_frame. This mode requires intermediate_frames set to True.
  • bool intermediate_frames: If False, stream only direct parent_frame->child_frame transforms (no matter if they were originally direct neighbors). If True, stream all the transforms between parent_frame and all child_frames.
  • duration publication_period: How often to publish the transforms.
  • bool allow_transforms_update: If true, periodically checks for updates in subtree topology. Can even handle cases when parent_frame isn't reachable at the time of the request. Default is false.
  • int32 publisher_queue_size: Queue size of the transform publisher.
  • string requested_topic_name: If nonempty, the stream will be published on the given topic. Leads to an error if another stream is only registered on this topic with incompatible settings.
  • string requested_static_topic_name: If nonempty, specifies the name of the stream with static transforms. Defaults to $(requested_topic_name)/static.

Example usage


    <param name="buffer_size" value="30.0"/>
    <param name="publish_frame_service" value="true"/>
    <param name="use_node_namespace" value="true"/>
    <node name="tf_server" pkg="tf2_server" type="tf2_server_node">
        <param name="transforms_update_period" value="10.0" />
                    parent_frame: 'odom'
                    child_frames: ['base_link']
                    intermediate_frames: True
                    publication_period: 0.02
                    publisher_queue_size: 10
                    allow_transforms_update: True

C++ client

This C++ client code shows how to subscribe the whole TF subtree under the base_link frame. The transforms in the buffer get updated once every 0.1 s.

#include <tf2_server/tf2_subtree_listener.h>

RequestTransformStreamRequest req;
req.parent_frame = "base_link";
req.child_frames = { };
req.intermediate_frames = true;
req.publisher_queue_size = 10;
req.publication_period = ros::Duration(0.1);

tf2_ros::Buffer buffer;
TransformSubtreeListener listener(req, buffer, false, ros::Duration(10));


buffer.canTransform("base_link", "left_track", ros::Time(0));

Python client

This Python client example shows how to subscribe exactly two transforms: base_link->left_track and base_link->front_left_flipper_endpoint. No other transforms are transmitted to the client.

req = RequestTransformStreamRequest()
req.parent_frame = "base_link"
req.child_frames = ["left_track", "front_left_flipper_endpoint"]
req.intermediate_frames = False
req.publisher_queue_size = 10
req.publication_period = rospy.Duration(0.1)

buffer = Buffer()
listener = TransformSubtreeListener(req, buffer, max_server_wait=rospy.Duration(10))


buffer.can_transform("base_link", "left_track", rospy.Time(0))

Connect a node to an already existing transform stream

    <!-- This assumes you've already requested a TF subtree "odom", e.g. by putting it in the `streams` parameter. -->
    <node name="my_node" pkg="any_pkg" type="node">
        <remap from="/tf" to="tf2_server/streams/odom" />
        <remap from="/tf_static" to="tf2_server/streams/odom/static" />

Principle of working of the subtree listener/publisher

The TransformSubtreeListener classes hide some implementation details from the user. Here we describe what exactly happens when a subtree is requested.

First, service ~/request_transform_stream is called with the given subtree configuration. The server responds with a message that specifies topic_name and static_topic_name, which are autogenerated topic names from namespace ~/streams/*. The client then remaps /tf and /tf_static to these topics and subscribes to them.

On the server side, the autogenerated topics are cached and when a new client asks for an already published subtree configuration, the already existing topic names are returned. Each unique subtree configuration starts a timer in the server node, which publishes the requested transforms on the requested rate. When last client with a given configuration disconnects from its topics, the timer is stopped so that it doesn't eat resources. But the topic remains and anyone can connect later, which will start the timer again.


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