Cloud robotics

Cloud robotics is a field of robotics that attempts to invoke cloud technologies such as cloud computing, cloud storage, and other Internet technologies centered on the benefits of converged infrastructure and shared services for robotics. When connected to the cloud, robots can benefit from the powerful computation, storage, and communication resources of modern data center in the cloud, which can process and share information from various robots or agent (other machines, smart objects, humans, etc.). Humans can also delegate tasks to robots remotely through networks. Cloud computing technologies enable robot systems to be endowed with powerful capability whilst reducing costs through cloud technologies. Thus, it is possible to build lightweight, low-cost, smarter robots with an intelligent "brain" in the cloud. The "brain" consists of data center, knowledge base, task planners, deep learning, information processing, environment models, communication support, etc.
Components.
A cloud for robots potentially has at least six significant components:
Research.
 was funded by the European Union's Seventh Framework Programme for research, technological development projects, specifically to explore the field of cloud robotics. The goal of RoboEarth is to allow robotic systems to benefit from the experience of other robots, paving the way for rapid advances in machine cognition and behaviour, and ultimately, for more subtle and sophisticated human-machine interaction. RoboEarth offers a Cloud Robotics infrastructure. RoboEarth’s World-Wide-Web style database stores knowledge generated by humans – and robots – in a machine-readable format. Data stored in the RoboEarth knowledge base include software components, maps for navigation (e.g., object locations, world models), task knowledge (e.g., action recipes, manipulation strategies), and object recognition models (e.g., images, object models). The RoboEarth Cloud Engine includes support for mobile robots, autonomous vehicles, and drones, which require much computation for navigation.
Rapyuta is an open source cloud robotics framework based on RoboEarth Engine developed by the robotics researcher at ETHZ. Within the framework, each robot connected to Rapyuta can have a secured computing environment (rectangular boxes) giving them the ability to move their heavy computation into the cloud. In addition, the computing environments are tightly interconnected with each other and have a high bandwidth connection to the RoboEarth knowledge repository.
KnowRob is an extensional project of RoboEarth. It is a knowledge processing system that combines knowledge representation and reasoning methods with techniques for acquiring knowledge and for grounding the knowledge in a physical system and can serve as a common semantic framework for integrating information from different sources.
 is a large-scale computational system that learns from publicly available Internet resources, computer simulations, and real-life robot trials. It accumulates everything robotics into a comprehensive and interconnected knowledge base. Applications include prototyping for robotics research, household robots, and self-driving cars. The goal is as direct as the project's name—to create a centralised, always-online brain for robots to tap into. The project is dominated by Stanford University and Cornell University. And the project is supported by the National Science Foundation, the Office of Naval Research, the Army Research Office, Google, Microsoft, Qualcomm, the Alfred P. Sloan Foundation and the National Robotics Initiative, whose goal is to advance robotics to help make the United States more competitive in the world economy.
MyRobots is a service for connecting robots and intelligent devices to the Internet. It can be regarded as a social network for robots and smart objects (i.e. Facebook for robots). With socialising, collaborating and sharing, robots can benefit from those interactions too by sharing their sensor information giving insight on their perspective of their current state.
 is funded by the INTERREG IVA France (Channel) – England European cross-border co-operation programme. The project aims to develop new technologies for handicapped people through social and technological innovation and through the users' social and psychological integrity. Objectives is to produce a cognitive ambient assistive living system with Healthcare cluster in cloud with domestic service robots like humanoid, intelligent wheelchair which connect with the cloud.
ROS (Robot Operating System) provides an eco-system to support cloud robotics. ROS is a flexible and distributed framework for robot software development. It is a collection of tools, libraries, and conventions that aim to simplify the task of creating complex and robust robot behaviour across a wide variety of robotic platforms. A library for ROS that is a pure Java implementation, called rosjava, allows Android applications to be developed for robots. Since Android has a booming market and billion users, it would be significant in the field of Cloud Robotics.
DAVinci Project is a proposed software framework that seeks to explore the possibilities of parallelizing some of the robotics algorithms as Map/Reduce tasks in Hadoop. The project aims to build a cloud computing environment capable of providing a compute cluster built with commodity hardware exposing a suite of robotic algorithms as a SaaS and share data co-operatively across the robotic ecosystem. This initiative is not available publicly.
C2RO (C2RO Cloud Robotics) is a platform that processes real-time applications such as collision avoidance and object recognition in the cloud. Previously, high latency times prevented these applications from being processed in the cloud thus requiring on-system computational hardware (e.g. Graphics Processing Unit or GPU). C2RO published a peer-reviewed paper at IEEE PIMRC17 showing its platform could make autonomous navigation and other AI services available on robots- even those with limited computational hardware (e.g. a Raspberry Pi)- from the cloud. C2RO eventually claimed to be the first platform to demonstrate cloud-based SLAM (simultaneous localization and mapping) at RoboBusiness in September 2017.
Noos is a cloud robotics service, providing centralised intelligence to robots that are connected to it. The service went live in December 2017. By using the Noos-API, developers could access services for computer vision, deep learning, and SLAM. Noos was developed and maintained by Ortelio Ltd.
Rocos is a centralized cloud robotics platform that provides the developer tooling and infrastructure to build, test, deploy, operate and automate robot fleets at scale. Founded in October 2017, the platform went live in January 2019.
Limitations of cloud robotics.
Though robots can benefit from various advantages of cloud computing, cloud is not the solution to all of robotics.
Challenges.
The research and development of cloud robotics has following potential issues and challenges:
History.
The term "Cloud Robotics" first appeared in the public lexicon as part of a talk given by James Kuffner in 2010 at the IEEE/RAS International Conference on Humanoid Robotics entitled "Cloud-enabled Robots".
 Since then, "Cloud Robotics" has become a general term encompassing the concepts of information sharing, distributed intelligence, and fleet learning that is possible via networked robots and modern cloud computing. Kuffner was part of Google when he delivered his presentation and the technology company has teased its various cloud robotics initiatives until 2019 when it launched the Google Cloud Robotics Platform for developers.
From the early days of robot development, it was common to have computation done on a computer that was separated from the actual robot mechanism, but connected by wires for power and control. As wireless communication technology developed, new forms of experimental "remote brain" robots were developed controlled by small, onboard compute resources for robot control and safety, that were wirelessly connected to a more powerful remote computer for heavy processing.
The term "cloud computing" was popularized with the launch of Amazon EC2 in 2006. It marked the availability of high-capacity networks, low-cost computers and storage devices as well as the widespread adoption of hardware virtualization and service-oriented architecture.
In a correspondence with Popular Science in July 2006, Kuffner wrote that after a robot was programmed or successfully learned to perform a task it could share its model and relevant data with all other cloud-connected robots:
Some publications and events related to Cloud Robotics (in chronological order):