Worst-Case Latency Analysis of Message Synchronization in ROS

Multi-sensor data fusion is crucial for modern autonomous systems to accurately perceive their surrounding environments and make intelligent decisions. However, as different sensor sources may have significant time disparity, it is necessary to synchronize their data before sending them to the fusion algorithm, in order to control such differences and get meaningful fusion results. This paper discusses the message synchronization policy in ROS, a popular framework for robotic systems. The ROS message synchronization policy has proven to be highly effective in reducing the time disparity, but it introduces a certain level of latency. Therefore, to use it for real-time systems, it is essential to establish an upper bound for the worst-case latency that may occur. Specifically, we analyze two key latency metrics of the ROS message synchronization policy, the passing latency and reaction latency, which are needed to analyze the end-to-end delay and reaction time on the system level. We conduct experiments under different settings to evaluate the precision of our proposed latency upper bounds against the maximum observed latency in real execution.