> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.stereolabs.com/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.stereolabs.com/_mcp/server. # Adding Positional Tracking in ROS > **Warning** > > **The ZED ROS Wrapper packages are no longer maintained** because ROS 1 reached [end-of-life (EOL) on 2025-05-31](https://www.ros.org/blog/noetic-eol/) with the final Noetic release. > > We recommend upgrading to [ROS 2](/docs/integrations/ros-2) to take advantage of the latest ZED SDK features for robotics applications. ## Position with RViz In this tutorial, you will learn in detail how to configure your own RViz session to see only the position data information that you require. RViz provides plugins for visualizing the camera's pose and its path over time. ### Camera odometry The `Odometry` plugin provides a clear visualization of the odometry of the camera (`nav_msgs/Odometry`) in the Odometry frame. ![Odometry](/_fern-img/500bcab6879014a0d49c9ff48ce0a8581fbaa575e5b809128173988896b79dd3.webp) Key parameters: * `Topic`: Selects the odometry topic `/zed/zed_node/odom` * `Unreliable`: Check this to reduce the latency of the messages * `Position tolerance` and `Angle tolerance`: set both to `0` to be sure to visualize all positional data * `Keep`: Set to the number of messages to visualize at a time * `Shape`: You can visualize odometry information as an arrow pointing in the direction of the `X` axis, or as a three `Axes` frame. Both shapes can be resized to your preference As of ZED SDK v2.6, pose covariance is available if the `pos_tracking/area_memory` parameter is set to `false` in the `params/common.yaml` file. ![Covariance](/_fern-img/a70b310daeb89cad54ad6a91a767d5f50edb987845da8aba46b0af707cdaf7d3.webp) You can get a visual estimation of the covariance with the odometry plugin by checking the `Covariance` option. The position covariance is visualized as an ellipsoid centered in the camera frame. The three orientation covariances are visualized as three 2D ellipses centered on the corresponding axis. You can change the `Scale` factors to get a better visualization when the ellipsoid and the ellipses are too big (high covariance) or not visible (low covariance). ### Camera pose The `Pose` plugin provides a visualization of the position and orientation of the camera (`geometry_msgs/PoseStamped`) in the Map frame similar to the `Odometry` plugin, but the `Keep` parameter and the `Covariance` parameter are not available. The `Topic` to be subscribed to is `/zed/zed_node/pose`. ![Pose](/_fern-img/c53eac390a326830fd9c2a29ad760caff2c8d69275cbbd3da3868a755043c706.webp) ![Pose with Covariance](/_fern-img/a89ea2592005dd8fbab138426d1f9b4df61719fa99ffeabdf70e1cb0bfa63b78.webp) ### Camera path The ZED wrapper provides two different paths for the camera position and orientation: * `/zed/zed_node/path_map`: The history of the camera pose in Map frame * `/zed/zed_node/path_odom`: The history of the odometry of the camera in Map frame ![Paths](/_fern-img/7207f1b7c7e3114175aa592caf3cc820dff8c2ab028df2d50b53284d8f745866.webp) Above you can see both the `Pose` (green) and the `Odometry` (red) paths. The `odometry pose` is calculated with a visual odometry algorithm (visual-inertial for the camera models with an IMU when `pos_tracking/imu_fusion` is `true`) as the sum of the movement from one step to the next. It is therefore affected by drift. The `camera pose` is instead continuously fixed using the StereoLabs tracking algorithm that combines visual information, spatial memory information and, for the camera models with an IMU, inertial information. The parameters to be configured are analogous to the parameters seen above for the `Pose` and `Odometry` plugins. ## Position subscribing in C++ In this tutorial, you will learn how to write a simple C++ node that subscribes to messages of type `geometry_msgs/PoseStamped` and `nav_msgs/Odometry` to retrieve the position and the orientation of the ZED camera in the `Map` and in the `Odometry` frames. ### Introduction Use the following command to connect the ZED camera to the ROS network: * **ZED:** ```bash roslaunch zed_wrapper zed.launch ``` * **ZED Mini:** ```bash roslaunch zed_wrapper zedm.launch ``` * **ZED 2:** ```bash roslaunch zed_wrapper zed2.launch ``` * **ZED 2i:** ```bash roslaunch zed_wrapper zed2i.launch ``` * **ZED X:** ```bash roslaunch zed_wrapper zedx.launch ``` * **ZED X Mini:** ```bash roslaunch zed_wrapper zedxm.launch ``` The ZED node starts to publish messages about its position in the network only if there is another node that subscribes to the corresponding topic. > **Note** > > The code below subscribes to topics in the `/zed/zed_node` namespace used by `zed.launch`. With the other launch files, the namespace is named after the camera model (for example `/zed2i/zed_node`): change the topic names in the code or remap them when running the node. The ZED wrapper publishes two kinds of positions: * `odometry`: The position is calculated as the sum of the movements relative to the previous position. It uses visual odometry, fused with the inertial data for the camera models with an IMU. * `pose`: The position calculated relative to the `world map`. Historical information about the environment and inertial data (for the camera models with an IMU) are fused to get a better 6 DoF pose. The ROS wrapper follows ROS [REP105](http://www.ros.org/reps/rep-0105.html) conventions. ### Running the tutorial If you properly followed the [ROS Installation Guide](/docs/integrations/ros/#installation), the executable of this tutorial has just been compiled and you can run the subscriber node using the following command: ```bash rosrun zed_tracking_sub_tutorial zed_tracking_sub ``` If the ZED node is running and a camera is connected or you have loaded an SVO file, you will receive the following stream of messages confirming that you are correctly subscribing to the ZED pose and odometry topics: ```bash [ INFO] [1536571277.284918933]: Received odom in 'odom' frame : X: 0.01 Y: 0.11 Z: 0.27 - R: -59.13 P: 29.17 Y: -38.27 [ INFO] [1536571277.308147447]: Received pose in 'map' frame : X: -0.02 Y: -0.04 Z: 0.03 - R: -3.36 P: -4.32 Y: -12.08 [ INFO] [1536571277.328975670]: Received odom in 'odom' frame : X: 0.03 Y: 0.11 Z: 0.28 - R: -62.26 P: 29.26 Y: -37.74 [ INFO] [1536571277.344163358]: Received pose in 'map' frame : X: -0.03 Y: -0.02 Z: 0.03 - R: -1.21 P: -1.00 Y: -13.21 [ INFO] [1536571277.372976799]: Received odom in 'odom' frame : X: 0.04 Y: 0.12 Z: 0.28 - R: -65.35 P: 27.69 Y: -36.27 [ INFO] [1536571277.375593051]: Received pose in 'map' frame : X: -0.04 Y: -0.01 Z: 0.02 - R: -0.24 P: 1.28 Y: -14.98 [ INFO] [1536571277.408942979]: Received pose in 'map' frame : X: -0.06 Y: -0.01 Z: 0.03 - R: -0.85 P: 2.67 Y: -17.63 [ INFO] [1536571277.416963850]: Received odom in 'odom' frame : X: 0.06 Y: 0.13 Z: 0.29 - R: -68.11 P: 26.79 Y: -33.93 [ INFO] [1536571277.417057266]: Received odom in 'odom' frame : X: 0.07 Y: 0.14 Z: 0.29 - R: -69.27 P: 25.64 Y: -29.91 [ INFO] [1536571277.442988345]: Received pose in 'map' frame : X: -0.05 Y: -0.01 Z: 0.03 - R: -0.85 P: 2.67 Y: -17.63 [ INFO] [1536571277.465031616]: Received odom in 'odom' frame : X: 0.09 Y: 0.16 Z: 0.30 - R: -72.27 P: 24.17 Y: -28.24 [ INFO] [1536571277.476189234]: Received pose in 'map' frame : X: -0.06 Y: -0.00 Z: 0.03 - R: -0.85 P: 2.66 Y: -17.63 [ INFO] [1536571277.476251272]: Received odom in 'odom' frame : X: 0.10 Y: 0.18 Z: 0.31 - R: -75.13 P: 23.33 Y: -25.71 [ INFO] [1536571277.509004649]: Received pose in 'map' frame : X: -0.07 Y: -0.01 Z: 0.04 - R: -2.80 P: 5.82 Y: -17.74 [ INFO] [1536571277.516935704]: Received odom in 'odom' frame : X: 0.11 Y: 0.19 Z: 0.31 - R: -73.16 P: 20.36 Y: -20.36 [ INFO] [1536571277.543752689]: Received pose in 'map' frame : X: -0.08 Y: -0.02 Z: 0.06 - R: -4.38 P: 7.86 Y: -17.73 [ INFO] [1536571277.561048985]: Received odom in 'odom' frame : X: 0.11 Y: 0.19 Z: 0.31 - R: -70.84 P: 16.76 Y: -14.78 [ INFO] [1536571277.575540826]: Received pose in 'map' frame : X: -0.09 Y: -0.02 Z: 0.07 - R: -5.79 P: 9.17 Y: -17.61 [ INFO] [1536571277.605050948]: Received odom in 'odom' frame : X: 0.10 Y: 0.20 Z: 0.32 - R: -68.37 P: 12.53 Y: -9.49 [...] ``` If you move your camera by hand, you will see how the position and orientation are updated in real time, and how `odom` and `pose` drift apart from each other because the `odom` pose is pure odometry data and is not corrected. ### The code ```C #include #include #include #include "tf2/LinearMath/Quaternion.h" #include "tf2/LinearMath/Matrix3x3.h" #include #define RAD2DEG 57.295779513 /** * This tutorial demonstrates receiving ZED odom and pose messages over the ROS system. */ /** * Subscriber callbacks */ void odomCallback(const nav_msgs::Odometry::ConstPtr& msg) { // Camera position in map frame double tx = msg->pose.pose.position.x; double ty = msg->pose.pose.position.y; double tz = msg->pose.pose.position.z; // Orientation quaternion tf2::Quaternion q( msg->pose.pose.orientation.x, msg->pose.pose.orientation.y, msg->pose.pose.orientation.z, msg->pose.pose.orientation.w); // 3x3 Rotation matrix from quaternion tf2::Matrix3x3 m(q); // Roll Pitch and Yaw from rotation matrix double roll, pitch, yaw; m.getRPY(roll, pitch, yaw); // Output the measure ROS_INFO("Received odom in '%s' frame : X: %.2f Y: %.2f Z: %.2f - R: %.2f P: %.2f Y: %.2f", msg->header.frame_id.c_str(), tx, ty, tz, roll * RAD2DEG, pitch * RAD2DEG, yaw * RAD2DEG); } void poseCallback(const geometry_msgs::PoseStamped::ConstPtr& msg) { // Camera position in map frame double tx = msg->pose.position.x; double ty = msg->pose.position.y; double tz = msg->pose.position.z; // Orientation quaternion tf2::Quaternion q( msg->pose.orientation.x, msg->pose.orientation.y, msg->pose.orientation.z, msg->pose.orientation.w); // 3x3 Rotation matrix from quaternion tf2::Matrix3x3 m(q); // Roll Pitch and Yaw from rotation matrix double roll, pitch, yaw; m.getRPY(roll, pitch, yaw); // Output the measure ROS_INFO("Received pose in '%s' frame : X: %.2f Y: %.2f Z: %.2f - R: %.2f P: %.2f Y: %.2f", msg->header.frame_id.c_str(), tx, ty, tz, roll * RAD2DEG, pitch * RAD2DEG, yaw * RAD2DEG); } /** * Node main function */ int main(int argc, char** argv) { // Node initialization ros::init(argc, argv, "zed_tracking_subscriber"); ros::NodeHandle n; // Topic subscribers ros::Subscriber subOdom = n.subscribe("/zed/zed_node/odom", 10, odomCallback); ros::Subscriber subPose = n.subscribe("/zed/zed_node/pose", 10, poseCallback); // Node execution ros::spin(); return 0; } ``` ### The code explained The following is a brief explanation of the source code above. ```C void poseCallback(const geometry_msgs::PoseStamped::ConstPtr& msg) { // Camera position in map frame double tx = msg->pose.position.x; double ty = msg->pose.position.y; double tz = msg->pose.position.z; // Orientation quaternion tf2::Quaternion q( msg->pose.orientation.x, msg->pose.orientation.y, msg->pose.orientation.z, msg->pose.orientation.w); // 3x3 Rotation matrix from quaternion tf2::Matrix3x3 m(q); // Roll Pitch and Yaw from rotation matrix double roll, pitch, yaw; m.getRPY(roll, pitch, yaw); // Output the measure ROS_INFO("Received pose in '%s' frame : X: %.2f Y: %.2f Z: %.2f - R: %.2f P: %.2f Y: %.2f", msg->header.frame_id.c_str(), tx, ty, tz, roll * RAD2DEG, pitch * RAD2DEG, yaw * RAD2DEG); } ``` The two callbacks are very similar; the only difference is that `poseCallback` receives messages of type `geometry_msgs/PoseStamped` and `odomCallback` receives messages of type `nav_msgs/Odometry`. These are similar but not identical. However, the information extracted from the two topics is the same: camera position and camera orientation. ```C double tx = msg->pose.position.x; double ty = msg->pose.position.y; double tz = msg->pose.position.z; ``` Extracting the position is straightforward since the data is stored in a `geometry_msgs/Point` structure with three floating-point fields (`x`, `y`, `z`). ```C // Orientation quaternion tf2::Quaternion q( msg->pose.orientation.x, msg->pose.orientation.y, msg->pose.orientation.z, msg->pose.orientation.w); // 3x3 Rotation matrix from quaternion tf2::Matrix3x3 m(q); // Roll Pitch and Yaw from rotation matrix double roll, pitch, yaw; m.getRPY(roll, pitch, yaw); ``` Extracting the orientation is less straightforward as it is published as a quaternion vector. To convert the quaternion to a more readable form, we must first convert it to a 3x3 rotation matrix from which we can finally extract the three values for Roll, Pitch and Yaw in radians. ```C ROS_INFO("Received pose in '%s' frame : X: %.2f Y: %.2f Z: %.2f - R: %.2f P: %.2f Y: %.2f", msg->header.frame_id.c_str(), tx, ty, tz, roll * RAD2DEG, pitch * RAD2DEG, yaw * RAD2DEG); ``` Finally, we can print the information received to the screen after converting the radian values to degrees. The `main` function is very standard and is explained in detail in the ["Talker/Listener" ROS tutorial](http://wiki.ros.org/ROS/Tutorials/WritingPublisherSubscriber%28c%2B%2B%29). It is important to note how the subscribers are defined: ```C // Subscribers ros::Subscriber subOdom = n.subscribe("/zed/zed_node/odom", 10, odomCallback); ros::Subscriber subPose = n.subscribe("/zed/zed_node/pose", 10, poseCallback); ``` A `ros::Subscriber` is a ROS object that listens on the network and waits for its own topic message to be available. When a message is received, it executes the callback assigned to it. In this tutorial, we declared two subscribers to the pose data: * The subscriber to the topic `/zed/zed_node/odom` calls the `odomCallback` function when it receives a message of type `nav_msgs/Odometry` that matches that topic * The subscriber to the topic `/zed/zed_node/pose` calls the `poseCallback` function when it receives a message of type `geometry_msgs/PoseStamped` that matches that topic ### Conclusion The full source code of this tutorial is available on GitHub in the [zed\_tracking\_sub\_tutorial](https://github.com/stereolabs/zed-ros-examples/tree/master/tutorials/zed_tracking_sub_tutorial) sub-package. Along with the node source code, you can find the `package.xml` and `CMakeLists.txt` files that complete the tutorial package.