Cloud Robotics and Automation
What if robots and automation systems were not limited by onboard
computation, memory, or programming? This is now possible
with wireless networking and rapidly expanding Internet resources. In 2010,
James Kuffner at Google introduced the term "Cloud Robotics" to
describe a new approach to robotics that takes advantage of the
Internet as a resource for massively parallel computation and
sharing of vast data resources.
The Google autonomous
driving project exemplifies this approach: the system indexes maps and
images that are collected and updated by satellite, Streetview, and
crowdsourcing to facilitate accurate localization.
Another example is Kiva Systems new approach to warehouse automation
and logistics using large numbers of mobile platforms to move pallets
using a local network to coordinate planforms and update tracking
data. These are just two new projects that build on resources from the
Steve Cousins of Willow Garage aptly summarized the idea: "No
robot is an island." Cloud Robotics recognizes the wide availability
of networking, incorporates elements of open-source, open-access, and
crowdsourcing to greatly extend earlier concepts of "Online Robots"
and "Networked Robots".
Cloud Robotics has potential to improve performance in at least
five ways: 1) Big Data: indexing a global library of images, maps, and
object data, 2) Cloud Computing: parallel grid computing on demand for
statistical analysis, learning, and motion planning, 3) Open-Source /
Open-Access: humans sharing code, data, algorithms, and hardware
designs, 4) Collective Robot Learning: robots sharing trajectories,
control policies, and outcomes, and 5) Crowdsourcing and call centers:
offline and on-demand human guidance for evaluation, learning, and
T-ASE Special Issue on Cloud Robotics and Automation. Papers Due Jan 31, 2014.
Panel at SxSW on Cloud Robotics. Austin, TX, US. Mar 2014.
IROS Workshop on Cloud Robotics. Tokyo. Nov 2013.
CASE 2013 Workshop on Cloud Manufacturing and Automation.
Cloud-Based Robot Mapping. June 2013.
Vlad Usenko, Markus Waibel,
Mohanarajah Gajamohan, Dominique Hunziker, Dhananjay Sathe, Mayank Singh.
Cloud-Based Robot Grasping with the Google Object Recognition Engine.
Ben Kehoe, Akihiro Matsukawa, Sal Candido, James Kuffner, and Ken Goldberg.
IEEE International Conference on Robotics and Automation. Karlsruhe, Germany. May 2013.
US National Science Foundation Workshop on Cloud Robotics: Challenges and Opportunities, Feb 2013.
- Cloud Robotics and Automation: A Survey of Related
Work. K. Goldberg and B. Kehoe. EECS Department, University of
California, Berkeley, Technical Report UCB/EECS-2013-5. January 2013.
Romo: $150 cloud-enabled robot from Romotive.
"USD 10 Robot" Design Challenge Winners.
Results of an open design competition for an affordable robot for K-12 education, 2012.
Organized by the African Robotics Network.
Toward Cloud-Based Grasping with Uncertainty in Shape: Estimating
Lower Bounds on Achieving Force Closure with Zero-Slip Push
Ben Kehoe, Dmitry Berenson, Ken Goldberg. IEEE International
Conference on Robotics and Automation. May 2012.
Cloud Robotics: Connected to the Cloud, Robots Get Smarter
Erico Guizzo. IEEE Spectrum. 2011.
In June 2011, President
Obama announced the
U.S. National Robotics Initiative,
$70M for new research.
ROS in Java for
Robots using Android phones and tablets by Damon Kohler (Google Munich), 2011.
RoboEarth - A World Wide Web for Robots
Markus Waibel, Raffaello D'Andrea et al. 2011.
Willow Garage and Google announce ROS Java Library for Cloud Robotics, 2011.
Cloud-Enabled Robots, James J. Kuffner. IEEE-RAS International
Conference on Humanoid Robotics. 2010.
Platform for Robotics Research Based on the Remote-Brained Robot
Approach. Masayuki Inaba, Satoshi Kagami, Fumio Kanehiro, Yukiko
Hoshino, Hirochika Inoue. International Journal of Robotics Research
(IJRR) 2000, 19:933. (Earlier papers from Inaba et al about this idea
date back to 1993).