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

Abstract

Mobility, power, and price points often dictate that robots do not have sufficient computing power on board to run modern 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. In this paper, we present FogROS 2, an easy-to-use, open-source platform to facilitate cloud and fog robotics that is compatible with the emerging Robot Operating System 2 (ROS 2) standard. FogROS 2 provisions a cloud computer, deploys and launches ROS 2 nodes to the cloud computer, sets up secure networking between the robot and cloud, and starts the application running. FogROS 2 is completely redesigned and distinct from its predecessor to support ROS 2 applications, transparent video compression and communication, improved performance and security, support for multiple cloud-computing providers, and remote monitoring and visualization. We demonstrate in example applications that the performance gained by using cloud computers can overcome the network latency to significantly speed up robot performance. In examples, FogROS 2 reduces SLAM latency by 50%, reduces grasp planning time from 14s to 1.2s, and speeds up motion planning 28x. When compared to alternatives, FogROS 2 reduces network utilization by up to 3.8x. FogROS 2, source, examples, and documentation is available at https: //github.com/BerkeleyAutomation/FogROS2.

The Cloud-to-Edge-to-IoT Continuum as an Enabler for Search and Rescue Operations

“…Companies started investing in the field as they recognized the large potential of cloud robotics. This led to the first open-source cloud robotics frameworks appearing in recent years [13]. An example of this is the solution from Rapyuta Robotics (Available online: https://www.rapyuta-robotics.…”

“…This limitation makes the task of creating large-scale and advanced robotics applications much harder to achieve. The current state of cloud platforms does not support the actual robotic application needs off the shelf [13][14][15][16][17]. It includes bi-directional data flow, multi-process applications or exposing sockets outside the cloud environment.…”

XBot2D: towards a robotics hybrid cloud architecture for field robotics

“…A similar approach is taken by AWS Greengrass ( Kurniawan, 2018 ). Using proprietary interfaces, as reported in Ichnowski et al (2022) , Rapyuta and Greengrass allow building and deploying an entire pipeline for robotics applications, as in Mohanarajah et al (2015b) , Mouradian et al (2018b) , from a centralized cloud interface. Computing environments are private, secure, optimized for data transmission, and can be connected to build parallel architectures.…”