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Mobility, power, and price points often dictate that robots do not havesufficient computing power on board to run contemporary robot algorithms atdesired rates. Cloud computing providers such as AWS, GCP, and Azure offerimmense computing power and increasingly low latency on demand, but tappinginto that power from a robot is non-trivial. We present FogROS2, an open-sourceplatform to facilitate cloud and fog robotics that is included in the RobotOperating System 2 (ROS 2) distribution. FogROS2 is distinct from itspredecessor FogROS1 in 9 ways, including lower latency, overhead, and startuptimes; improved usability, and additional automation, such as region andcomputer type selection. Additionally, FogROS2 gains performance, timing, andadditional improvements associated with ROS 2. In common robot applications,FogROS2 reduces SLAM latency by 50 %, reduces grasp planning time from 14 s to1.2 s, and speeds up motion planning 45x. When compared to FogROS1, FogROS2reduces network utilization by up to 3.8x, improves startup time by 63 %, andnetwork round-trip latency by 97 % for images using video compression. Thesource code, examples, and documentation for FogROS2 are available athttps://github.com/BerkeleyAutomation/FogROS2, and is available through theofficial ROS 2 repository at https://index.ros.org/p/fogros2/.

FogROS2: An Adaptive Platform for Cloud and Fog Robotics Using ROS 2