Fog Robotics

Fog Robotics

"Fog Robotics" (April 2018): Robot systems that efficiently distribute computation and memory between edge, gateway, and cloud devices to address privacy and security (in analogy with Fog Computing). - Ken Goldberg, UC Berkeley.

Secure Fog Robotics Using the Global Data Plane (August 2018): US National Science Foundation project to investigate security issues for "Fog Robotics" led by UC Berkeley researchers.

Cloud Robotics

Robots and automation systems are no longer limited by onboard resources in computation, memory, or software. "Cloud Robotics and Automation" is a new paradigm where robots and automation systems share data and code and perform computation via networks building on emerging research in cloud computing, Deep Learning, Big Data, open-source software, and government/industry initiatives such as the "Internet of Things", "Smarter Planet", "Industrial Internet", "Industry 4.0.", and "Made in China 2025".

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.

Aside: I feel the Singularity is distracting attention from a far more realistic concept: Multiplicity. In contrast to a mythical monolithic AI that will supercede humans, Multiplicity characterizes an emerging category of systems where diverse groups of humans work together with diverse groups of machines to address difficult problems in search, transportation, healthcare, design, and discovery. Multiplicity combines the wisdom of crowds with the power of cloud computing and is exemplified by many Cloud Robotics and Automation systems.

Oct 2018: Google announces that they are developing an open-access Cloud Robotics platform to "combine the power of AI, robotics, and the cloud" that will be available in 2019.

Sept 2018: Anki begins shipping the Vector the first home/consumer Cloud Robot with substantial infrastructure for voice recognition and Cloud-based computation and learning.