Cloud Robotics and Automation
What if robots and automation systems were not limited by onboard computation, memory, or software? Rather than viewing robots and automated machines as isolated systems with limited computation and memory, "Cloud Robotics and Automation" considers a new paradigm where robots and automation systems exchange data and perform computation via networks.
Extending earlier work that links robots to the Internet, Cloud Robotics and Automation
builds on emerging research in cloud computing, machine learning, big data, open-source software, and major industry initiatives in the "Internet of Things", "Smarter Planet", "Industrial Internet", and "Industry 4.0."
Consider Google's autonomous car. It uses the network to index maps, images, and data on prior driving trajectories, weather, and traffic to determine spatial localization and make decisions. Data from each car is shared via the network for statistical optimization and machine learning performed by grid computing in the Cloud. Another example is Kiva Systems approach to warehouse automation and logistics using large numbers of mobile platforms to move pallets using a local network to coordinate platforms and share updates on floor conditions.
Google's James Kuffner coined the term "Cloud Robotics" in 2010. Cloud Robot and Automation systems can be broadly defined as any robot or automation system that relies on data or code from a network to support its operation, i.e., where not all sensing, computation, and memory is integrated into a single standalone system.
There are at least four potential advantages to using the Cloud: 1) Big Data: access to updated libraries of images, maps, and object/product data, 2) Cloud Computing: access to parallel grid computing on demand for statistical analysis, learning, and motion planning, 3) Collective Learning: robots and systems sharing trajectories, control policies, and outcomes, and 4) Human Computation: use of crowdsourcing to tap human skills for analyzing images and video, classification, learning, and error recovery. The Cloud can also provide access to a) datasets, publications, models, benchmarks, and simulation tools, b) open competitions for designs and systems, and c) open-source software. It is important to recognize that Cloud Robotics and Automation raises critical new questions related to network latency, quality of service, privacy, and security.
The term "Singularity" is sometimes used to describe a punctuation point in the future where Artificial Intelligence (AI) surpasses human intelligence. The term was popularized by science fiction author Vernor Vinge and Ray Kurzweil. Superintelligence, a 2014 book by Nick Bostrom, explored similar themes that provoked Stephen Hawking, Elon Musk, and Bill Gates to issue warnings about the dangers of AI and robotics. My sense is that the Singularity is distracting attention from a far more realistic and important development that we might call "Multiplicity". Multiplicity characterizes an emerging category of systems where diverse groups of humans work together with diverse groups of machines to solve difficult problems. Multiplicity combines the wisdom of crowds with the power of cloud computing and is exemplified by many Cloud Robotics and Automation systems.
10 Breakthrough Technologies for 2016: Cloud Robotics.
MIT Tech Review. Apr 2016.
Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning
and Large-Scale Data Collection.
Sergey Levine, Peter Pastor, Alex Krizhevsky, Deirdre Quillen.
Arxiv pre-print. March 2016.
Privacy-Preserving Cloud-Based Grasp Planning.
Jeffrey Mahler, Brian Hou, Sherdil Niyaz, Florian T. Pokorny, Ramu Chandra, Ken Goldberg.
Submitted to IEEE International Conference on Automation Science and Engineering, (CASE), Dallas, TX. Aug 2016.
Cloud Robotics and Factory Automation.
MIT Tech Review. Apr 2016.
Cloud Robotics and Surgery.
MDDI Interview with Scott Huennekens of Verb Surgical.
Dex-Net 1.0: A Cloud-Based Network of 3D Objects for Robust Grasp
Planning Using a Multi-Armed Bandit Model with Correlated Rewards.
Jeffrey Mahler, Florian T. Pokorny, Brian Hou, Melrose Roderick, Michael Laskey, Mathieu Aubry, Kai Kohlhoff, Torsten Kroeger, James Kuffner, Ken Goldberg.
IEEE International Conference on Robotics and Automation, (ICRA), Stockholm, Sweden. May 2016.
A Survey of Research on Cloud Robotics and Automation.
Ben Kehoe, Sachin Patil, Pieter Abbeel, Ken Goldberg.
IEEE Transactions on Automation Science and Engineering (T-ASE): Special
Issue on Cloud Robotics and Automation. Vol. 12, no. 2. Apr. 2015.
Special Issue on Cloud Robotics and Automation (11 papers).
IEEE Transactions on Automation Science and Engineering (T-ASE). Apr 2015.
Robots with Their Heads in the Clouds.
Medium.com, from Aspen Ideas Festival Talk. Posted Aug 2014.
New Research Center Aims to Develop Second Generation of Surgical Robots. John Markoff, NY Times, Oct, 2014.
The Robot in the Cloud: A Conversation With Ken Goldberg.
Quentin Hardy, NY Times, Oct, 2014
The RoboBrain Project. Aug 2014.
Cloud Robotics. The Atlantic, by Megan Garber.
DARPA on Cloud Robotics. April 2014.
Big Push in Robotics Now Seems Imminent.
The Economist. 29 March 2014.
(Cloud Robotics discussed in last section).
NPR Science Friday by Jordan Davidson. 26 March 2014.
(Cloud Robotics discussed in last section).
T-ASE Special Issue on Cloud Robotics and Automation.
Submissions now closed: To Appear in 2015.
Open Call for References for new Survey Paper on Cloud Robotics and Automation.
Moments that Stood out at SXSW: Panel on Cloud Robotics and Automation. Wall Street Journal, 11 March 2014.
Panel on Cloud Robotics and Automation with James Kuffner of Google, Ayorkor Korsah of Ashesi Univ in Ghana, and Ken Goldberg, UC Berkeley.
SXSW. Austin, TX, US. Mar 9, 2014.
IROS Workshop on Cloud Robotics. Tokyo. Nov 2013.
Cloud Robotics in "Why We Love Robots."
Short Documentary Film including section on Cloud Robotics.
(Nominated for Emmy Award and winner of Botscar Award at Robot Film Festival), Oct 2013.
CASE 2013 Workshop on Cloud Manufacturing and Automation. Aug 2013.
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 Humanoid Robots, James J. Kuffner. IEEE-RAS International
Conference on Humanoid Robotics. 2010.
IEEE RAS Technical Committee on Networked Robots
Beyond Webcams: An Introduction to Online Robots. MIT Press. 2001.
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.