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2020, International Journal for Research in Applied Science and Engineering Technology IJRASET
https://doi.org/10.22214/ijraset.2020.6319…
6 pages
1 file
Nowadays, with the rapidly increasing use of cloud services, there are many opportunities and challenges faced in the industry. One of the trending domains is Cloud Robotics and Automation. Cloud Robotics deals with the cloud technologies such as Cloud Computing, Cloud Storage and Networking and other internet technologies. With the help of these cloud services, robots can be remotely controlled through the network. Also, Cloud Robotics and Automation makes it possible to build cost efficient and lightweight robots. Few of the challenges faced are developing a good knowledge base, establishing a proper communication network, effective load balancing, preventing data privacy and security and dealing with the ethical problems. The purpose of this study is to understand the scope of Cloud Robotics and Automation, how it can help to reduce human efforts in an effective way by overcoming the above-mentioned challenges. The study covers different types of technologies widely being used since 2015 that includes Cloud data storage, Networking, Cloud Computing, Artificial Intelligence, Deep Learning, Internet of Things. The study definitely answers the scope of the domain and gives precise examples of how it has helped in reducing human efforts by overcoming various challenges.
Advances in Information Security, Privacy, and Ethics
This chapter highlights the total structure and capabilities of robotic systems. This chapter then discusses the invocation of cloud technology in robotics technology empowering the whole system with higher processing power and bigger storage unit which was not possible earlier in the conventional robotic system being restricted in on-board manipulation. The flexibility of handling big data, ability to perform cloud computing, crowed sourcing and collaborative robot learning using the cloud robotics technology has been discussed briefly. This chapter describes concepts of Cloud Enabled Standalone Robotic System (CeSRS), Cloud Enabled Networked Robotic System (CeNRS), Cloud Robotic Networking System (CRNS), Standalone Robotic System (SRS), Common Networked Robotic (CNRS), Infrastructure As A Service (IAAS), Multi Robot System, R/R and R/C Network, ROS, Tele Operated Robotic System, Quality of Service (QoS), Virtual Machine (VM) and Cloud Datacenter. The existing applications of the c...
—The Cloud infrastructure and its extensive set of Internet-accessible resources has potential to provide significant benefits to robots and automation systems. We consider robots and automation systems that rely on data or code from a network to support their operation, i.e., where not all sensing, computation , and memory is integrated into a standalone system. This survey is organized around four potential benefits of the Cloud: 1) Big Data: access to libraries of images, maps, trajectories, and descriptive data, 2) Cloud Computing: access to parallel grid computing on demand for statistical analysis, learning, and motion planning, 3) Collective Robot Learning: robots 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 improve robots and automation systems by providing access to a) datasets, publications, models, benchmarks, and simulation tools, b) open competitions for designs and systems, and c) open-source software. This survey includes over 150 references on results and open challenges. A website with new developments and updates is available at: Note to Practitioners—Most robots and automation systems still operate independently using onboard computation, memory, and programming. Emerging advances and the increasing availability of networking in the " Cloud " suggests new approaches where processing is performed remotely with access to dynamic global datasets to support a range of functions. This paper surveys research to date.
Springer Nature Singapore Pte Ltd, 2020
Cloud is Internet-based utility computing which offers a choice to rent and use the computational resources on subscription basis. It has the service-oriented and deployment models which would provide suitable services to the end-users. Robotics can be defined as a machine which would do some useful works as given by the user which would reduce his/her work and make smooth transactions. Cloud robotics is an upcoming technological area with a combination of cloud computing and robotics. Interconnection of these two fields would profit the mankind. Many more different varieties of applications are emerging as on today. In coming of the days, cloud robots will have major role to perform, such as to improve the 'public utility of technology'. This paper describes the laws of robotics, characteristics of robotics, need for cloud robotics, initial steps for cloud robotics, available cloud robotic technologies, constraints on cloud robotics, cloud robotics architectures, addressing needs of cloud robotics, cloud robotic algorithm-SLAM. This present paper would bring out a review of all such aspects which would benefit the reader with a fine tune.
The idea of cloud robotics attracts many researchers mind in the last few years. Cloud robotics is a term combination of cloud technologies with its mass and services which is combined to serve the huge use of robotics applications. The power of robotics is behind the power of cloud which aims in the process of learning and exchanging knowledge, the use of cloud to process heavy tasks allows use of smaller on-board computers in a robot which needs to perform tasks in an accurate real time. So in realistically the Cloud can make robots lighter, cheaper and smaller. This paper surveys cloud robotics in order to give a clear platform in this technology.
2013 IEEE 9th International Conference on Computational Cybernetics (ICCC), 2013
Cloud Robotics is an emerging field within robotics, currently covering various application domains and robot network paradigms. This paper provides a structured, systematic overview of the numerous definitions, concepts and technologies linked to Cloud Robotics and cloud technologies in a broader sense. It also presents a roadmap for the near future, describing development trends and emerging application areas. Cloud Robotics may have a significant role in the future as an explicitly human-centered technology, capable of addressing the dire needs of our society.
Indonesian Journal of Electrical Engineering and Computer Science, 2017
Cloud robotics is an emerging field that is centred on the benefits of converged infrastructure and shared services of a cloud computing environment. In this paper, a system is designed with an autonomous Pick and Place robot to sense environmental data such as temperature and Motion, along with GPS coordinates and sends them on the cloud. The mobile robot is controlled using an LPC1764 microcontroller and communicates with the cloud via a CC3200 Launchpad. A private cloud is set up using Open Stack that provides Infrastructure as a Service. The collected data are stored in a cloud server which could be viewed through a mobile app and can be used to create awareness about the environmental changes of the location under study. A proof-of-concept prototype has been developed to illustrate the effectiveness of the proposed system.
Recently, robots and automation systems have been at the front of research with the majority of systems still operating independently using onboard computation, memory manipulation and communication. With improvements in communication technology and the increasing availability of network, new approaches where robot and automation processing is performed remotely with access to large scale datasets, support a range of functions. Cloud Robotics supplements performance enhancement of robotics and autonomous systems by providing a global infrastructure in innovative ways. This paper summarizes recent research into five traits of Cloud Robotics for performance enhancement in robotics and autonomous systems: 1) Remote Brain, 2) Big Data and Shared Knowledge-base, 3) Collective Learning, 4) Intelligence and Behavior, and 5) Cloud architectures. Towards the end, in this survey, we present future directions for research in cloud robotics.
Ijca Proceedings on National Conference Cum Workshop on Bioinformatics and Computational Biology, 2014
The application of the cloud computing concept to robots is called Cloud Robotics. It is a concept that utilizes the services of the cloud so that robots can have learning abilities. Since applications for Cloud Robotics have to be developed in a platform, majority of the cloud application developers choose ROS for it. Robot Operating System (ROS) is an open source middleware that has a collection of inter-programming language headers to allow the sharing of data between independent programs. ROS provides a graph-like structure for cloud robotics. A new 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 a huge leap in the field of Cloud Robotics.
HIGH-ENERGY PROCESSES IN CONDENSED MATTER (HEPCM 2020): Proceedings of the XXVII Conference on High-Energy Processes in Condensed Matter, dedicated to the 90th anniversary of the birth of RI Soloukhin, 2020
Disaster management requires fast and efficient handling of information. To deal with this issue, it does not only involve humans as the primary resource but also the various tools involved, such as robots. Cloud robotics extends the computation and information sharing among several types of robots so that robots can work as teamwork to complete a mission. This paper provides an overview of cloud robotics implementation to help deal with disasters that occur. Robots are used to mapping disaster-affected areas, identifying objects, and sending data real-time to the cloud server. This paper also discusses the implementation of typical network architecture on disaster case using fog computing paradigm. We propose using the MQTT protocol for information distribution from the robot side to the cloud server. We compare its performance with the HTTP protocol. The latest challenges and problems are also discussed in this paper.
Lecture Notes in Electrical Engineering, 2020
The robotics field is widely used in the industrial domain, but nowadays several other domains could also take advantage of it. This interdisciplinary branch of engineering requires the use of human interfaces, efficient communication systems, high storage and processing capabilities, among other issues, to perform complex tasks. This paper aims to propose a cloud-based framework platform for robot operation in a hospital environment, addressing some challenges, such as communications security and processing/storage features. The recent developments in the artificial intelligence field and cloud resources sharing are allowing the penetration of robots in unstructured environments. However, some new challenges and solutions need to be tested in real environments. Our main contribution is to decrease the time-consumption related to processing and storage costs, associated with the physical processing resources of the robots. Also, the proposed methods provide an increase of the processing variables that are not yet present in the physical resources, such as in the case of robots with limited processing time or storage capabilities. This paper presents a platform based on Cloud Computing with services to support processing, storage and analytics applied to hospital environments. The proposed platform enables to achieve a decrease in the timeconsumption, especially when it is intended to retrieve information about all robot activities.
Companion Proceedings of the10th International Conference on Utility and Cloud Computing, 2017
Robots are moving out of factories, service robotics is bringing them to our homes, work environments, cities, and outdoors. While the Robot Operating System (ROS) is promising to open the world of robotics to developers, a proper platform and ecosystem supporting robotic applications development is still missing. This work presents an example of cloud robotics application in which cloud computing is not just complementing limited robot capabilities, but is leveraged to provide a development and operations environment supporting the complete life-cycle of a robotics-enabled application. We relate on our experience building cloud robotics applications spanning heterogeneous hardware (i.e., robots and cloud servers) through a use case scenario.
2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC), 2018
Due to the various advantages that the cloud can offer to robots, there has been the recent emergence of the cloud robotics paradigm. Cloud robotics permits robots to unload computing and storage related tasks into the cloud, and as such, robots can be built with smaller on-board computers. The use of cloud-robotics also allows robots to share knowledge within the community over a dedicated cloud space. In order to build-up robots that benefit from the cloud-robotics paradigm, different cloud-robotics platforms have been released during recent years. This paper critically reviews and compares existing cloud robotic platforms in order to provide recommendations on future use and gaps that still need to be addressed. To achieve this, 8 cloud robotic platforms were investigated. Key findings reveal varying underlying architectures and models adopted by these platforms, in addition to different features offered to end-users.
IEEE Network, 2000
We extend the computation and information sharing capabilities of networked robotics by proposing a cloud robotic architecture. The cloud robotics architecture leverages the combination of a virtual ad-hoc cloud formed by machine-to-machine (M2M) communications among participating robots, and an infrastructure cloud enabled by machine-to-cloud (M2C) communications. Cloud robotics utilizes elastic computing models, in which resources are dynamically allocated from a shared resource pool in the cloud, to support task offloading and information sharing in robotic applications. We propose communication protocols, and several elastic computing models to handle different applications. We discuss the technical challenges in computation, communications and security, and illustrate the potential benefits of cloud robotics in several applications.
2018 International Conference on Intelligent and Innovative Computing Applications (ICONIC), 2018
Advances in robotics and cloud computing have led to the emergence of cloud robotics where robots can benefit from remote processing, greater memory and computational power, and massive data storage. The integration of robotics and cloud computing has often been regarded as a complex aspect due to the various components involved in such systems. In order to address this issue, different studies have attempted to create cloud robotic architectures to simplify representation into different blocks or components. However, limited study has been undertaken to critically review and compare these architectures. As such, this paper investigates and performs a comparative analysis of existing cloud robotic architectures in order to identify key limitations and recommend on the future of cloud robotic architectures. As part of this study, 7 such architectures have been reviewed and compared and results showed limited evaluation of existing architectures in favour of security weaknesses.
2016 World Automation Congress (WAC), 2016
The paper proposes a software architecture for cloud robotics which intends three subsystems in the cloud environment: Middleware Subsystem, Background Tasks Subsystem, and Control Subsystem. The architecture invokes cloud technologies such as cloud computing, cloud storage, and other networking platforms arranged on the assistances of congregated infrastructure and shared services for robotics, for instance Robot Operating System (ROS). Since the architecture is looking for reliable, scalable, and distributed system for the heterogeneous large-scale autonomous robots, Infrastructure as a Service (IaaS) is chosen among the cloud services. Three major tasks can be handled by the proposed software architecture Computing, Storage, and Networking. Hadoop-MapReduce provides the appropriate framework in the cloud environment to process and handle these tasks.
IOP Conference Series: Materials Science and Engineering, 2018
In recent years, with the development of science and technology, new technologies have emerged continuously, such as cloud computing, big data, etc., and cloud computing technology has been used in robot research, making the designed robot have high real-time performance and high energy efficiency, low cost and a series of advantages. Among robot technologies, controlling robots is one of the key technologies. One of the classical problems in the field of robots is the synchronous map construction and positioning (SLAM) problem. This problem is a typical computationally intensive task. In traditional robots, the implementation method is to rely on the robot's local computing resources to calculate and solve in real time. The disadvantages of this method are slow speed, low precision, and very large computational overhead. This paper aims at the current research status, based on the robot architecture and the "Software as a Service" (SaaS) idea in cloud computing, proposes a SLAM service framework based on cloud computing, and studies the control in the robot, and finally the development of cloud computing and robotics is looking into the future.
Electronics
With the development of computer technology and artificial intelligence (AI), service robots are widely used in our daily life. At the same time, the manufacturing cost of the robots is too expensive for almost all small companies. The greatest technical limitations are the design of the service robot and the resource sharing of the robot groups. Path planning for robots is one of the issues playing an important role in every application of service robots. Path optimization, fast computation, and minimum computation time are required in all applications. This paper aims to propose the Google Cloud Computing Platform and Amazon Web Service (AWS) platforms for robot path planning. The aim is to identify the effect and impact of using a cloud computing platform for service robots. The cloud approach shifts the computation load from robots to the cloud server. Three different path-planning algorithms were considered to find the path for robots using the Google Cloud Computing Platform, ...
IEEE Access
Networked robotics involves a collection of robots working together to perform complex tasks, such as search and rescue task in disaster management. Because such tasks are beyond the capacity of a single powerful robot, networked robotics has been widely researched. However, the modes of cooperation in traditional networked robotics have been restricted by the inherent physical constraint that all computations are performed in the robotic network, with knowledge sharing being limited to the collective storage in the network. Cloud robotics, which allows robots to benefit from the rich storage, computation, and communication resources of modern data centers, is widely accepted as a promising approach to efficient robot cooperation in applications, such as disaster management. In this paper, we study robotic cooperation in cloud robotics. We first give a conceptual view of the nature of this cooperation. We then propose three novel robotic cooperation frameworks for cloud robotics: robotic knowledge sharing cooperation, robotic physical-task cooperation, and robotic computation task cooperation. Finally, we identify several critical challenges, and illustrate the potential benefits of robotic cooperation in cloud robotics. INDEX TERMS Cloud robotics, multi-robot system, robot cooperation, quality of service.
2015
Cloud seeding in cloud robotics is the concept of forming an adhoc cloud using the available robot resources. A team of robots working in the same field utilizing cloud robotics might experience a connection failure to the main node however this should not stop field work. The teamed robots surrender their resources to form a virtual adhoc cloud not only to load balance tasks but to share resources and information. In this paper the researcher explores further on how cloud seeding can best be done, the security implications as well as networking concerns involved. This however is not a permanent infrastructure but a way of circumventing the challenge of network failure between the main cloud infrastructure and the field robots in cloud robotics.
2010 IEEE International Conference on Robotics and Automation, 2010
We propose DAvinCi, a software framework that provides the scalability and parallelism advantages of cloud computing for service robots in large environments. We have implemented such a system around the Hadoop cluster with ROS (Robotic Operating system) as the messaging framework for our robotic ecosystem. We explore the possibilities of parallelizing some of the robotics algorithms as Map/Reduce tasks in Hadoop. We implemented the FastSLAM algorithm in Map/Reduce and show how significant performance gains in execution times to build a map of a large area can be achieved with even a very small eight-node Hadoop cluster. The global map can later be shared with other robots introduced in the environment via a Software as a Service (SaaS) Model. This reduces the burden of exploration and map building for the new robot and minimizes it's need for additional sensors. Our primary goal is to develop a cloud computing environment which provides a compute cluster built with commodity hardware exposing a suite of robotic algorithms as a SaaS and share data cooperatively across the robotic ecosystem.
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