Cloud robotics is a field of robotics that
attempts to invoke cloud technologies such as cloud computing, cloud storage, and other
Internet technologies centred around the benefits of converged infrastructure
and shared services for robotics. When connected to the cloud, robots can
benefit from the powerful computational, storage, and communications resources
of modern data centre 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 have intelligent
"brain" in the cloud. The "brain" consists of data center, knowledge base, task planners, deep learning, information processing,
environment models, communication support etc.[1][2][3][4]
Cloud Robots Paradigm
Contents
·
6 Risks
Components
·
Offering a
global library of images, maps, and object data, often with geometry and
mechanical properties, expert system, knowledge base (i.e. semantic web, data
centres)；
·
Massively-parallel
computation on demand for sample-based statistical modelling and motion
planning, task planning, multi-robot collaboration, scheduling and coordination
of system；
·
Robot
sharing of outcomes, trajectories, and dynamic control policies and robot
learning support；
·
Human
sharing of "open-source" code, data, and designs for programming,
experimentation, and hardware construction；
·
On-demand
human guidance and assistance for evaluation, learning, and error recovery;
·
Augmented
human robot interaction through various way (Semantics knowledge base, Apple
SIRI like service etc.).
Applications
Autonomous mobile
robots: Google's self-driving
cars are cloud robots.
The cars use the network to access Google's enormous database of maps and
satellite and environment model (like Streetview) and combines it with
streaming data from GPS, cameras, and 3D sensors to monitor its own position
within centimetres, and with past and current traffic patterns to avoid
collisions. Each car can learn something about environments, roads, or driving,
or conditions, and it sends the information to the Google cloud, where it can
be used to improve the performance of other cars.
Cloud Self-driving Car
Cloud medical robots: a medical cloud (also called healthcare cluster)
consists of various service such as disease archive, electronic medical
records, patient health management system, practice service, analytics service,
clinic solutions, expert system etc. A robot can connect to the cloud to
provide clinic service to penitents as well as delivery assistance to doctors
such as co-surgery robot. Moreover, it also provides collaboration service by
sharing information for doctors, care giver in clinic treatment.[6]
Cloud Clinic Robot Paradigm
Assistive robots: A domestic robot can be employed for healthcare and
life monitoring for elderly people. The system collects the health status of
users and exchange information with cloud expert system or doctors to
facilitate elderly peoples life, especially for those with chronic diseases. For
example, the robots are able to provide support to prevent the elderly from
falling down, emergency healthy support such as heart disease, blooding
disease. Care givers of elderly people can also get notification when in
emergency from the robot through network.[7]
Industrial robots: As highlighted by the Germany Industry 4.0 Plan
"Industry is on the threshold of the fourth industrial revolution. Driven
by the Internet, the real and virtual worlds are growing closer and closer
together to form the Internet of Things. Industrial production of the future
will be characterised by the strong individualisation of products under the
conditions of highly flexible (large series) production, the extensive
integration of customers and business partners in business and value-added
processes, and the linking of production and high-quality services leading to
so-called hybrid products." [8] In manufacturing, such cloud based robot systems could
learn to handle tasks such as threading wires or cables, or aligning gaskets
from professional knowledge base. A group of robots can share information for
some collaborative tasks. Even more, a consumer is able to order customised
product to manufacturing robots directly with online order system.[9] Another potential paradigm is shopping-delivery robot
system- once an order is placed, a warehouse robot dispatches the item to an
autonomous car or autonomous drone to delivery it to its recipient (see Figure Cloud Self-driving Car ).
Research
RoboEarth [10] 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 lots of computation for
navigation.[11]
Rapyuta [12] 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.[13]
KnowRob [14] 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.
RoboBrain [15] 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 Cornel 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.[16]
MyRobots is a service for connecting robots and intelligent
devices to the Internet.[17] 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.
COALAS [18] 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.[7]
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.[19]
Limitations of cloud
robotics
Though robots can
benefit from various advantages of cloud computing, cloud is not the solution
to all of robotics.[20]
·
Controlling
a robot’s motion which relies heavily on sensors and feedback of controller
won’t benefit much from the cloud.
·
Cloud-based
applications can get slow or unavailable due to low-latency responses or
network hitch. If a robot relies too much on the cloud, a fault in the network
could leave it “brainless.”
·
Tasks that
involve real-time execution require on-board processing.
Challenges
·
Scalable
parallelisation-grid-based computing, parallelisation schemes scale with the
size of automation infrastructure.
·
Effective
load balancing: Balancing operations between local and cloud computation.
·
Knowledge
bases and representations
·
Collective
learning for automation in cloud
·
Infrastructure/Platform
or Software as a Service
·
Internet
of Things for robotics
·
Integrated
and collaborative fault tolerant control
·
Big Data:
Data, collected and/or disseminated over large, accessible networks can enable
decisions for classification problems or reveal patterns.
·
Wireless
communication, Connectivity to the cloud
·
System
architectures of robot cloud
·
Open-source,
open-access infrastructures
·
Workload
Sharing
·
Standards
and Protocol
Risks
Environmental security - The concentration of computing resources and users in a
cloud computing environment also represents a concentration of security
threats. Because of their size and significance, cloud environments are often
targeted by virtual machines and bot malware, brute force attacks, and other
attacks.
Data privacy and
security - Hosting
confidential data with cloud service providers involves the transfer of a
considerable amount of an organisation's control over data security to the
provider. For example, every cloud contains a huge information from the clients
include personal data. If a household robot is hacked, users could have risk of
their personal privacy and security, like house layout, life snapshot,
home-view, etc. It may be accessed and leaked to the world around by criminals.
Another problems is once a robot is hacked and controlled by someone else,
which may put the user in danger.
Ethical problems - Some ethics of robotics, especially for cloud based
robotics must be considered. Since a robot is connected via networks, it has
risk to be accessed by other people. If a robot is out of control and carries
out illegal activities, who should be responsible for it.
History
Special Issue on Cloud
Robotics and Automation- A special issue of the IEEE Transactions on Automation
Science and Engineering, April 2015.[1]
Robot APP Store Robot
Applications in Cloud, provide applications for robot just like computer/phone
app.[23]
A Roadmap for U.S.
Robotics From Internet to Robotics 2013 Edition- by Georgia Institute of
Technology, Carnegie Mellon University Robotics Technology Consortium,
University of Pennsylvania, University of Southern California, Stanford
University, University of California–Berkeley, University of Washington,
Massachusetts Institute of TechnologyUS and Robotics OA US. The Roadmap
highlighted “Cloud” Robotics and Automation for Manufacturing in the future
years.[20]
National Robotics
Initiative of US announced in 2011 aimed to explore how robots can enhance the
work of humans rather than replacing them. It claims that next generation of
robots are more aware than oblivious, more social than solitary.[26]
James J. Kuffner, a
former CMU robotics professor, and now research scientist at Google, spoke on
cloud robotics in IEEE/RAS International Conference on Humanoid Robotics 2010.
It describes "a new approach to robotics that takes advantage of the
Internet as a resource for massively parallel computation and sharing of vast
data resources."[27]
Ryan Hickman, a Google
Product Manager, led an internal volunteer effort in 2010 to connect robots
with the Google's cloud services.This work was later expanded to include open
source ROS support and was demonstrated on stage by Ryan Hickman, Damon Kohler,
Brian Gerkey, and Ken Conley at Google I/O 2011.[28]
Cloud Robotics-Enable
cloud computing for robots. The author proposed some paradigms of using cloud
computing in robotics. Some potential field and challenges were coined. R. Li
2009.[4]
The IEEE RAS Technical
Committee on Internet and Online Robots was founded by Ken Goldberg and Roland
Siegwart et al. in May 2001. The committee then expanded to IEEE Society of
Robotics and Automation's Technical Committee on Networked Robots in 2004.[29]
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