FogROS2: An Adaptive Platform for Cloud and Fog Robotics Using ROS 2
Jeffrey Ichnowski, Kaiyuan Chen, Karthik Dharmarajan, Simeon Adebola, Michael Danielczuk, Víctor Mayoral-Vilches, Nikhil Jha, Hugo Zhan, Edith Llontop, Derek Xu, John Kubiatowicz, Ion Stoica, Joseph Gonzalez, Ken Goldberg
To appear at IEEE International Conference on Robotics and Automation (ICRA), 2023.
Abstract
Mobility, power, and price points often dictate that robots do not have sufficient computing power on board to run contemporary robot algorithms at desired rates. Cloud computing providers such as AWS, GCP, and Azure offer immense computing power on demand, but tapping into that power from a robot is non-trivial. We present FogROS2, an open-source platform to facilitate cloud and fog robotics that is compatible with the emerging Robot Operating System 2 (ROS 2) standard. FogROS2 is completely redesigned and distinct from its predecessor FogROS1 in 9 ways, and has lower latency, overhead, and startup times; improved usability, and additional automation, such as region and computer type selection. Additionally, FogROS2 was added to the official distribution of ROS 2, gaining performance, timing, and additional improvements associated with ROS 2. In examples, FogROS2 reduces SLAM latency by 50%, reduces grasp planning time from 14 s to 1.2 s, and speeds up motion planning 28x. When compared to FogROS1, FogROS2 reduces network utilization by up to 3.8x, improves startup time by 63%, and network round-trip latency by 97% for images using video compression.