TY - GEN
T1 - Worst-Case Time Disparity Analysis of Message Synchronization in ROS
AU - Li, Ruoxiang
AU - Guan, Nan
AU - Jiang, Xu
AU - Guo, Zhishan
AU - Dong, Zheng
AU - Lv, Mingsong
N1 - Funding Information:
This work is supported by the Research Grants Council of Hong Kong (GRF 11208522, 15206221) and the National Natural Science Foundation of China (NSFC 62102072). The authors also thank the anonymous reviewers for their helpful comments.
Publisher Copyright:
© 2022 IEEE.
PY - 2022/12
Y1 - 2022/12
N2 - Multi-sensor data fusion is essential in autonomous systems to support accurate perception and intelligent decisions. To perform meaningful data fusion, input data from different sensors must be sampled at time points in close propinquity to each other, otherwise the result cannot accurately reflect the status of the physical environment. ROS (Robotic Operating System), a popular software framework for autonomous systems, provides message synchronization mechanisms to address the above problem, by buffering messages carrying data from different sensors and grouping those with similar timestamps. Although message synchronization is widely used in applications developed based on ROS, little knowledge is known about its actual behavior and performance, so it is hard to guarantee the quality of data fusion. In this paper, we model the message synchronization policy in ROS and formally analyze its worst-case time disparity (maximal difference among the timestamps of the messages grouped into the same output set). We conduct experiments to evaluate the precision of the proposed time disparity upper bound against the maximal observed time disparity in real execution, and compare it with the synchronization policy in Apollo Cyber RT, another popular software framework for autonomous driving systems. Experiment results show that our analysis has good precision and ROS outperforms Apollo Cyber RT in terms of both observed worst-case time disparity and the theoretical bound.
AB - Multi-sensor data fusion is essential in autonomous systems to support accurate perception and intelligent decisions. To perform meaningful data fusion, input data from different sensors must be sampled at time points in close propinquity to each other, otherwise the result cannot accurately reflect the status of the physical environment. ROS (Robotic Operating System), a popular software framework for autonomous systems, provides message synchronization mechanisms to address the above problem, by buffering messages carrying data from different sensors and grouping those with similar timestamps. Although message synchronization is widely used in applications developed based on ROS, little knowledge is known about its actual behavior and performance, so it is hard to guarantee the quality of data fusion. In this paper, we model the message synchronization policy in ROS and formally analyze its worst-case time disparity (maximal difference among the timestamps of the messages grouped into the same output set). We conduct experiments to evaluate the precision of the proposed time disparity upper bound against the maximal observed time disparity in real execution, and compare it with the synchronization policy in Apollo Cyber RT, another popular software framework for autonomous driving systems. Experiment results show that our analysis has good precision and ROS outperforms Apollo Cyber RT in terms of both observed worst-case time disparity and the theoretical bound.
UR - http://www.scopus.com/inward/record.url?scp=85146119834&partnerID=8YFLogxK
U2 - 10.1109/RTSS55097.2022.00014
DO - 10.1109/RTSS55097.2022.00014
M3 - Conference article published in proceeding or book
AN - SCOPUS:85146119834
T3 - Proceedings - Real-Time Systems Symposium
SP - 40
EP - 52
BT - Proceeding - 43rd IEEE Real-Time Systems Symposium, RTSS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 43rd IEEE Real-Time Systems Symposium, RTSS 2022
Y2 - 5 December 2022 through 8 December 2022
ER -