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8th Conference on cloud Computing, Big Data and Emerging Topics

作者： Velasquez Villagran, Nancy Pesado, Patricia Estevez, Elsa Univ Nacl La Plata UNLP Fac Informat La Plata Argentina Univ Nacl UNS Dept Ciencias Ingn Computac Bahia Blanca Buenos Aires Argentina UNS CONICET Inst Ciencias Ingn Computac Bahia Blanca Buenos Aires Argentina

ISBN: (纸本)9783030612177;9783030612184

Robots in the industry have been used for decades, much before the so-called Fourth Industrial Revolution. They have been incorporated into industrial processes in various ways, for example, with mechanic arms, in assembly processes, welding, and painting, among others. Industrial robots are located in restricted access sites and their space is delimited by means of physical barriers and security measures. In recent years, Industry 4.0 proposes the use robots, able to collaborate with persons, known as collaborative robots or "cobots". Cobots are characterized by cooperating with human work, sharing the same workspace, and able to respond to simple human-machine interactions. In addition, given the benefits of applying cloud computing in Industry 4.0, research has been conducted in applying such technologies to robots. The approach is known as "cloud robotics" and appears as an emerging topic. The objective of this work is to carry out a systematic literature review of cloud robotics for Industry 4.0, in an attempt to present the state of the art in this field and identify opportunities for future research. From the analysis of the results, we observe an emerging interest in this area, and we identify main technologies applied, research themes, and application areas, as well as a special interest on security and safety aspects.

关键词： Industry 4.0 Industrial Internet of Things (IIoT) Internet of robotics Things (IoRT) cloud robotics Big data Machine learning Mobile robots <-

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A Platform for cloud robotics

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IFAC-PapersOnLine 2016年第30期49卷 48-53页

作者： do Nascimento, Amadeu Cardozo, Eleri Souza, Ricardo S. Guimarães, Eliane G. School of Electrical and Computer Engineering University of Campinas CampinasSP Brazil

This paper presents the evolution of a software platform for supporting experimentation in mobile robotics as part of teaching and researching activities. Starting with Web-based laboratories (WebLabs) in the early 2000s the platform kept evolving according to the networking and distributed computing trends since then. In addition to the physical resources managed by the platform, the platform now is able to manage a pool of virtual machines as resources for experimentation. This new class of resources brings the processing power as required by many modern mobile robotics applications. Virtual machines can be widespread on a cluster of processors, on a private cloud computing infrastructure, or on a public cloud computing service. Like any other resource managed by the platform the access to the virtual machines is subjected to user authentication and authorization. A mechanism of user authentication and authorization based on federated identities (single-sign-on) allows the sharing resources maintained by different administrative domains. The paper emphasizes the current stage of the platform and a case study in mobile robotics localization. Localization, as many other mobile robotics algorithms, can employ parallelism at the cluster and cloud levels in order to improve speed, reliability, and scaling. © 2016

关键词： Authentication cloud computing Cluster computing Mobile robots Network security Robot programming robotics Virtual machine Wireless telecommunication systems cloud robotics Federated identity Physical resources Software platforms Tele robotics Telematics User authentication Web based laboratories

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A Platform for cloud robotics

A Platform for Cloud Robotics

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4th IFAC Symposium on Telematics Applications (TA)

作者： do Nascimento, Amadeu, Jr. Cardozo, Eleri Souza, Ricardo S. Guimaraes, Eliane G. Univ Estadual Campinas Sch Elect & Comp Engn Campinas SP Brazil

关键词： Telerobotics robot programming mobile robots telematics cloud robotics

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Efficient Delivery of robotics Programming Educational Content Using cloud robotics 7

Efficient Delivery of Robotics Programming Educational Conte...

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7th International Conference on robotics and Automation Engineering (ICRAE)

作者： Murphy, Sean Militano, Leonardo Toffetti, Giovanni Maurer, Remo Zurich Univ Appl Sci Zurich Switzerland

ISBN: (纸本)9781665489188

In this paper, we report on our use of cloud-robotics solutions to teach a robotics Applications Programming course at Zurich University of Applied Sciences (ZHAW). The usage of Kubernetes based cloud computing environment combined with real robots - turtlebots and Niryo arms - allowed us to: 1) minimize the set up times required to provide a Robotic Operating System (ROS) simulation and development environment to all students independently of their laptop architecture and OS;2) provide a seamless "simulation to real" experience preserving the exciting experience of writing software interacting with the physical world;and 3) sharing GPUs across multiple student groups, thus using resources efficiently. We describe our requirements, solution design, experience working with the solution in the educational context and areas where it can be further improved. This may be of interest to other educators who may want to replicate our experience.

关键词： cloud robotics Kubernetes Robotic Applications Edge Computing

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Towards a Distributed Computation Offloading Architecture for cloud robotics 15

Towards a Distributed Computation Offloading Architecture fo...

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15th IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC)

作者： Chaari, Rihab Cheikhrouhou, Omar Koubaa, Anis Youssef, Habib Hmam, Habib Univ Mannouba Prince Res Lab Manouba Tunisia Taif Univ Coll CIT At Taif Saudi Arabia Univ Sfax Comp & Embedded Syst Lab Sfax Tunisia Prince Sultan Univ Riyadh Saudi Arabia ISEP CISTER INESC TEC Porto Portugal Gaitech Robot Shanghai Peoples R China Univ Sousse Prince Res Lab Sousse Tunisia Univ Moncton Fac Engn Moncton NB E1A 3E9 Canada

ISBN: (纸本)9781538677476

cloud robotics is incessantly gaining ground, especially with the rapid expansion of wireless networks and Internet resources. In particular, computation offloading is emerging as a new trend, enabling robots with more powerful computation resources. It helps them to overcome the hardware and software limitations by leveraging parallel computing capabilities and the availability of large amounts of resources in the cloud. However, the performance gain of computation offloading in cloud robotics is still an ongoing research problem because of the conflicting factors that affect the performance. In this paper, we investigate this issue and we design a distributed cloud robotic architecture for computation offloading based on Kafka middleware as messaging broker. We experimentally validated our solution and tested its performance using image processing algorithms. Experimental results show a significant reduction in robot CPU load, as expected, with an increase in robot communication delays.

关键词： cloud robotics processing offloading distributed computing

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Multi-objective Computation Offloading for cloud robotics using NSGA-II 17

Multi-objective Computation Offloading for Cloud Robotics us...

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17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

作者： Chaari, Rihab Cheikhrouhou, Omar Koubaa, Anis Youssef, Habib Hamam, Habib Univ Sousse PRINCE Res Lab Sousse Tunisia Univ Sfax ENIS CES Lab Sfax Tunisia Polytech Inst Porto ISEP IPP Porto Portugal Univ Moncton Fac Engn Moncton NB Canada

ISBN: (纸本)9781665428545

With the emergence of cloud robotics, computation offloading presents a new trend in cloud computing that has been applied to robots;to provide them with resources for performing computationally intensive tasks. In most scientific research, the main objectives behind computation offloading are reducing energy consumption and minimizing the execution time of robotics applications. However, these two metrics are conflicting, and optimizing them simultaneously is challenging. Reducing energy consumption may lead to a rise in the completion time, and vice-versa. In this paper, we consider the problem of optimization of energy consumption and completion time in a cloud robotic system. We formulated the offloading decision as a multi-objective optimization problem. We further adapted the Non-dominated Sorting Genetic Algorithm (NSGA-II) to find a set of Pareto-optimal solutions. Through simulations, we demonstrated that our offloading solution can save 80% of the robot's energy consumption;and reduce 70% of the application completion time. We proved also the adaptability of the model against bandwidth changes.

关键词： cloud robotics Computation offloading Offloading decision Multi-objective optimization NSGA-II

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A Game Theoretical Bandwidth Allocation Mechanism for cloud robotics

A Game Theoretical Bandwidth Allocation Mechanism for Cloud ...

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10th World Congress on Intelligent Control and Automation (WCICA)

作者： Wang, Lujia Meng, Max Q. -H. Chinese Univ Hong Kong Dept Elect Engn Shatin Hong Kong Peoples R China

ISBN: (纸本)9781467313988

cloud robotics is currently driving interest in both academia and industry, since it would allow robots to off-load computation intensive tasks, combine with multiple robots and even download new skills. Bandwidth allocation is the fundamental and dominant task for resource sharing among users in cloud robotics. However, many technical challenges are still outstanding, since incast congestion happens in high-bandwidth and low-latency networks, when multiple synchronized users send data to a same receiver in parallel [1]. In this paper, we introduce a resource allocation framework for cloud robotics, and propose a game-theoretic problem formulation and linear pricing scheme of bandwidth allocation, we also implement a congestion control algorithm by using optimal parameters derived from the game-theoretic algorithm. Simulation results demonstrate that the proposed mechanism achieves better performance of bandwidth allocation in cloud robotics scenarios.

关键词： cloud robotics Resource Allocation Complete Information Pricing Scheme Congestion Control

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A Web services based solution for the NAO Robot in cloud robotics environment 4

A Web services based solution for the NAO Robot in Cloud Rob...

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4th International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Bouziane, Radhia Terrissa, Labib Sadek Brethe, Jean-Franois Ayad, Soheyb Kazar, Okba Univ Biskra LINFI Lab Dept Comp Sci POB 145 RP Biskra 07000 Algeria Univ Biskra LINFI Lab Biskra Algeria Univ LeHavre GREAH Lab Le Havre France LINFI Lab Biskra Algeria

ISBN: (纸本)9781509064656

Since a few years, the development of robots introduced the cloud Computing paradigm in robotics field as "cloud robotics" generation. This new concept allows robots to outsource computing capabilities over the cloud, whither the Computing involves extra power requirements that could reduce the duration of the process. In this paper, we outline a new cloud robotics architecture for NAO robots. Based on Robot Operating System (ROS) middleware, this approach integrates Web services technologies in a cloud Computing environment, in order to enable Nao robots to consume their packages as an on-demand solution (as a service).

关键词： cloud Computing cloud robotics NAO ROS Web services

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Data Acquisition Framework for cloud robotics 10

Data Acquisition Framework for Cloud Robotics

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IEEE 10th International Conference on Awareness Science and Technology (iCAST)

作者： Watanobe, Yutaka Yaguchi, Yuichi Miyaji, Toshimune Yamada, Ryuhei Naruse, Keitaro Univ Aizu Dept Comp Sci & Engn Aizu Wakamatsu Fukushima Japan

ISBN: (纸本)9781728138213

In cloud robotics environments, software components play important roles by acquiring data from heterogeneous devices and then performing context-aware computing with the help of knowledge bases organized by the data. However, there are numerous tasks that must be performed to create such components, their corresponding database schemas, services, and repositories, and these tasks can be burdensome for developers. In this paper, a framework for constructing a data acquisition system with integrated robotic technology components and modern web-based technologies is presented. Our proposed framework enables developers to construct a robot environment with data acquisition functionalities by defining scenarios in an ontology language. The framework is realized in such a way that allows it to automatically generate the required software components and their corresponding repositories, which are deployed on the cloud. A case study showcasing the proposed framework is also demonstrated.

关键词： cloud robotics Data acquisition robotics technology components

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Motion and Connectivity Aware Offloading in cloud robotics via Genetic Algorithm

Motion and Connectivity Aware Offloading in Cloud Robotics v...

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IEEE Global Telecommunications Conference (GLOBECOM)

作者： Rahman, Akhlaqur Jin, Jiong Cricenti, Antonio Rahman, Ashfaqur Panda, Manoj Swinburne Univ Technol Sch Software & Elect Engn Hawthorn Vic 3122 Australia CSIRO Data61 Sandy Bay Tas 7005 Australia Amrita Univ Amrita Sch Engn ECE Dept Coimbatore 641112 Tamil Nadu India

ISBN: (纸本)9781509050192

Task offloading opens a gateway for robotic applications to leverage computation support from the cloud infrastructure. It exploits a trade-off between the robot's and cloud's processing capabilities, and the communication between the two entities plays a critical role in making these decisions. Two major factors that significantly influence communication are network connectivity (bandwidth) and mobility of the robot. We integrate these two factors with the offloading decisions to formulate an optimization problem. Our objective in this paper is to improve the quality of service (QoS) for a 25 node application taskflow, known as direct acyclic graph. We propose a genetic algorithm based approach to solve the optimization problem which performs a novel three-layer decision making: (i) whether to offload a task or not, (ii) path planning to reach a desired location for offloading/local execution, (iii) select access point to associate with for offloading. We simulate for a smart city scenario consisting of 36-cell workspace with obstacles and compare the offloading results with a well-established fixed movement offloading method. The outcomes of our study suggest that motion and connectivity aware offloading leads to more efficient performance in terms of improved QoS and minimum consumption of resources, i.e., energy, time or distance.

关键词： cloud robotics Motion Planning Access Point Task Offloading Smart City Genetic Algorithm Internet of Things

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