ROS-FM: Fast Monitoring for the Robotic Operating System(ROS)

Abstract

In this paper, we leverage the newly integrated extended Berkely Packet Filters (eBPF) and eXpress Data Path (XDP) to build ROS-FM, a high-performance inline network-monitoring framework for ROS. We extend the framework with a security policy enforcement tool and distributed data visualization tool for ROS1 and ROS2 systems. We compare the overhead of this framework against the generic ROS monitoring tools, and we test the policy enforcement against existing ROS penetration testing tools to evaluate their effectiveness. We find that the network monitoring framework and the associated visualization tools outperform the existing ROS monitoring tools for all robots with more than 10 running processes and that the monitoring tool uses only 4% of the overhead of the generic tools for robots with 80 processes. We further demonstrate the effectiveness of the security tool against common attacks in both ROS1 and ROS2.