FogROS brings robotic cloud computing to the Robot Operating System
Ken Goldberg, with Jeffrey Ichnowski, Kaiyuan Chen, Karthik Dharmarajan, Simeon Adebola, Michael Danielczuk, Vıctor Mayoral-Vilches, Hugo Zhan, Derek Xu, Ramtin Ghassemi, John Kubiatowicz, Ion Stoica, Joseph Gonzalez, published "FogROS 2: An Adaptive and Extensible Platform for Cloud and Fog Robotics Using ROS 2" in Arxiv! Brian Heater from TechCrunch featured this groundbreaking research in the article "FogROS brings robotic cloud computing to the Robot Operating System."
From the article:
"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."
Goldberg notes that such a platform could open up even more possibilities for robotics than those listed above. “It can potentially benefit other compute-intensive tasks for robots such as stochastic planning and facilitate supervised and unsupervised deep learning of tasks from multiple robots.”