Advantech Robotic Suite/Time Sync Viewer

Introduction

Time Sync Viewer is a time synchronization detection tool specifically designed for ROS2, provided as an rqt plugin. It is used to monitor and analyze the synchronization status of multi-sensor data in real time. In robotics applications, ensuring accurate time synchronization is crucial, as it directly affects the performance and stability of technologies such as SLAM, deep learning, and sensor fusion. Time Sync Viewer provides synchronization detection, visual analysis, and detailed time statistics, helping developers quickly identify and resolve synchronization issues.

Features and Advantages:

• Multi-Sensor Timestamps Visualization: Visually displays the timestamps of multiple sensors to help users check data alignment.
• Time Synchronization Flag (sync_flag): Automatically triggers a flag when synchronization conditions are met, providing instant confirmation.
• Statistical Analysis: Calculates synchronization frequency, average time intervals, standard deviation, and other metrics to quantify performance.
• Sensor Check: Assists users in identifying hardware delays, network jitter, and data loss that may result in incomplete data.
• Improved Sensor Fusion: Enhances data consistency and stability for applications such as SLAM, robotic arms, drones, and AMRs.

Note: Time Sync Viewer is only supported on Ubuntu 22.04

GUI Description

Example Using Camera, IMU, and LiDAR

1. Time Axis Display
   • The image displays the timestamps of different data streams (topics), where each horizontal line represents a topic. Examples include:：
     • camera (camera image)
     • imu (IMU data)
     • lidar (LiDAR scan)
     • z_sync_flag (sync flag)
2. Synchronization Range
   • In this example, the sync_range is configured with 2ms, meaning that data points arriving within this 2-millisecond window are considered synchronized.
   • On the time axis, when a synchronization event is triggered, a sync_flag is marked.
3. Synchronization Analysis
   • When all sensor data points fall within the 2ms range, they are considered synchronized (sync).
   • The image displays multiple sync points, indicating that at those moments, the sensor data is properly synchronized.

Synchronization Statistics

It provides detailed time synchronization statistics, including the Monitoring Metrics Description:

Metric	Description
Sync Frequency	The number of times synchronized_callback is triggered per second (Hz).
Avg Interval	The average time interval between each callback (seconds).
Std Dev	The standard deviation of time intervals (seconds), indicating variability.
Max Interval	The maximum time interval, showing the longest delay.
Min Interval	The minimum time interval, showing the shortest synchronization time.

Monitoring results will be shown in the terminal

How to

• Step 1: Publish fake sensor data, including camera, IMU, and LiDAR(you can also use actual sensors)

In terminal 1, publish camera topic

cd /usr/local/Advantech/ros/humble/ros2-timesync-viewer/test/fake_sensor
python3 camera.py

In terminal 2, publish lidar topic

cd /usr/local/Advantech/ros/humble/ros2-timesync-viewer/test/fake_sensor
python3 lidar.py

In terminal 3, publish imu topic

cd /usr/local/Advantech/ros/humble/ros2-timesync-viewer/test/fake_sensor
python3 imu.py

• Step 2: Run Time Sync Viewer in Web UI, select "Utility" from the list on the left

• Step 3: Click launch button, then will open Time Sync Viewer window

• Step 4: Click start button

• Step 5: Select the topics that you want to view, then click OK

• Result: