On a recent trip to the Bay Area, I took a few hours to pay a visit to Berkeley Artificial Intelligence Research Lab (BAIR). Professor Ken Goldberg walked me around the lab and introduced me to a couple of projects the students have been working on. FogROS immediately grabbed my attention -- and not just because it sports a name similar to a problematic French cuisine.

Image Credits: Open Robotics

The offering arrives as part of the latest version of the open source Robotic Operating System, ROS 2 Humble Hawksbill -- the eight release of ROS 2. In a nutshell, it offers a method for offloading robotic tasks to a remote server, using a cloud computing platform like Amazon Web Services. Advances to server-side computing that have made things like cloud gaming possible with minimal latency can also be applied to robotics operations.

“Robots are often limited in their onboard computing capabilities due to weight and power requirements,” Jeff Ichnowski, a Berkeley post-doc student who headed up the project, told TechCrunch. “They also rarely have hardware accelerators like GPUs, TPUS or FPGAs. But many robot algorithms and recent advances (e.g. deep learning) benefit from high-end computers and hardware accelerators. We envision that using cloud computing to speed up slow computations can enable robots to do more things in the same amount of time.”

The platform being announced today as part of the new version of ROS is actually FogROS 2. Version one, which was introduced last summer, was an early proof-of-concept. This March, the teams quietly made a preview of FogROS 2 available through GitHub, and today it goes live for all, sporting a number of improvements designed to optimize cloud-based performance.

Image Credits: ROS

Much like playing Xbox games on a smartphone, the basic principle here is supplying a method to execute complex tasks on a robot that doesn’t require equally complex on-board processing. If you can complete the task via a remote server, you can save on size, weight and -- perhaps most importantly -- cost. The team notes in a recently published paper: