Source code on GitHub.


An autonomous robotics system needs to perceive itself, its environment, and plan its actions to achieve a task, and control those actions, in a closed loop. Perception is provided by a combination of sensors, for example camera, LIDAR, IMU, touch, motor positions, wheel ticks, and others. Each of these sensors operate independently running at different frequencies and many on their own clocks. This is a challenge when more than one sensor is needed to reconstruct an understanding of the environment for planning of actions.

Example of 10hz LIDAR, 30Hz camera, and 100hz IMU sensors operating concurrently.

A common practice is to use the system time as the clock on which all sensor data is tracked in a single timeline. When the sensor’s data is received, an interrupt occurs causing the software to record the sensor acquisition time as the current system time. This lacks accuracy as the current system time does not account for time spent transmitting the sensor data to the processor, or kernel delays in servicing the interrupt which records the system time. The acquisition time of the sensor data will be both late, and subject to jitter. For some applications this lack of accuracy in the single timeline for sensor data is a problem for a precise reconstruction of the environment and precise planning at higher action speeds.

The isaac_ros_correlated_timestamp_driver provides functionality for highly accurate acquisition time of sensor data translated to the system time. This is needed for precise reconstruction of the environment such as 3D maps, cost maps, and obstacle avoidance from multiple concurrent sensors. This enables high action speeds as multi-sensor perception has 2x orders of magnitude lower jitter (from 1ms to <10us).

This accuracy is provided by isaac_ros_correlated_timemestamp_driver by leveraging hardware features in Jetson platforms. A hardware feature uses TSC as the sensor acquisition time when an interrupt is received. This eliminates jitter in sensor acquisition time measurements caused by delays in the kernel servicing interrupts. This is used for camera, and IMU data in Nova. isaac_ros_correlated_timemestamp_driver converts TSC measurements to system time. In addition, time synchronization between system time, and Ethernet is maintained with PTP, using phc2sys. Hardware provides time synchronization between TSC and PTP, for highly precise sensor data acquisition times between camera and LIDAR sensors needed for sensor fusion in 3D reconstruction.


Set Up Development Environment

  1. Set up your development environment by following the instructions in getting started.

  2. Clone isaac_ros_common under ${ISAAC_ROS_WS}/src.

    cd ${ISAAC_ROS_WS}/src && \
       git clone
  3. (Optional) Install dependencies for any sensors you want to use by following the sensor-specific guides.


    We strongly recommend installing all sensor dependencies before starting any quickstarts. Some sensor dependencies require restarting the Isaac ROS Dev container during installation, which will interrupt the quickstart process.

Build isaac_ros_correlated_timestamp_driver

  1. Launch the Docker container using the script:

    cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
  2. Install the prebuilt Debian package:

    sudo apt-get install -y ros-humble-isaac-ros-correlated-timestamp-driver

Run Launch File

  1. Continuing inside the Docker container, launch the correlated timestamp driver:

    ros2 launch isaac_ros_correlated_timestamp_driver

Visualize Results

  1. Open a new terminal inside the Docker container:

    cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
  2. Output the timestamps:

    ros2 topic echo /correlated_timestamp


Isaac ROS Troubleshooting

For solutions to problems with Isaac ROS, see troubleshooting.



ros2 launch isaac_ros_correlated_timestamp_driver target_container:=<Target Container> nvpps_dev_file:=<NVPPS Dev Name> use_time_since_epoch:=<Use Time Since Epoch>


ROS Parameters

ROS Parameter







Use time since epoch.




NVPPS device name.

ROS Topics Published

ROS Topic





Timestamp correlation data.