Elsevier

Future Generation Computer Systems

Volume 74, September 2017, Pages 337-348
Future Generation Computer Systems

Robot Cloud: Bridging the power of robotics and cloud computing

https://doi.org/10.1016/j.future.2016.01.002Get rights and content

Highlights

  • The architecture design of a robot cloud is presented.

  • The simulation results show the advantage of our proposed scheduling algorithm and one big robot center.

  • The prototype system implementation shows the proposed idea is feasible and more such on-site services will be available in the future.

Abstract

Cloud computing is shaping the cyber world and evolves as a key computing and service platform for sharing resources including platforms, software applications and everything in the form of services. This is known “X as a Service”. Although it brings our age unparalleled computing ability and economic benefits, the application of cloud computing is still limited currently in the cyberspace due to the cloud services can only reside in cloud instead of our daily life environment. In fact, there are still a plethora of physical position based on-site service demands that cloud computing could help little due to the “cyber limitation”. In this paper, we aim to integrate the cyber world and the physical world by bringing up the idea of “Robot Cloud” to bridge the power of robotics and cloud computing. To make it possible, we design a novel Robot Cloud stack to support our idea and adopt the service-oriented architecture (SOA) to make the functional modules in the Robot Cloud more flexible, extensible and reusable. Then we develop a prototype of Robot Cloud using the popular Google App Engine to demonstrate our design method. Finally, we conduct the simulation experiments with a “robot show” application scenario to evaluate our scheduling policy and identify the effect of different request distributions and robot center solutions.

Introduction

Computing has been viewed as resources by human beings and used as the medium to build the powerful and versatile cyber world. To date, the vast majority of the applications in the computer technology are restricted to the interactions between human beings and cyberspace. The typical exemplar applications of such interactions include the Internet and the cloud computing technology.

Almost all users of the Internet are using a form of cloud computing  [1] although they may not realize it. Cloud computing enables people to store and access personal files, such as music, pictures, videos and bookmarks, to play games, and to use from anywhere the productivity applications deployed on remote servers instead of physically carrying around a storage medium installed with the applications.

As the cyber world mainly focuses on virtual applications and as the requests for application in the real world grow beyond the cyber domain, the existing cloud computing technology started to become insufficient to address the richness of the requests from the reality.

A robot is a mechanical intelligent agent which can perform tasks on its own, or with guidance. In other words, robots are usually guided by computer and electronic programs. However, three characteristics make robots to stand out as one of the best media that are able to act as the bridge between the virtual (cyber) world and reality. First, robots are of strong mobility. As robots are essentially machines, they are not confined to one physical location but have the capability to move around in their surroundings. Second, robots are perceivable. People endow robots the abilities of perceiving and absorbing data in the environment, processing data, and responding to various stimuli. The third character involves accuracy and reliability. Robots can perform certain tasks for humans and complete the work more accurately and efficiently.

Based on the merits of both robots and cloud computing technologies, in this paper we merge robots and cloud computing technologies and make the robot as one of the resources in the novel computing system named Robot Cloud. Our intention is to create synthetic systems which intensify the interaction between physical world and virtual world, making the best of both computation resources and robot resources to serve our human kind. In this novel architecture, Service-Oriented Architecture (SOA)  [2] plays an important role since a loosely coupled framework cannot only reuse existing assets easily, but also is conducive to the expansion and maintenance of the existing robot systems, achieve flexible response to customer requirement changes, maximize cost savings, and improve the efficiency of Robot Cloud.

Unlike James Kuffner’s cloud-enabled robotics  [3], the Robot Cloud is a system meeting people’s need and owning the ability to interact with the physical world. Considering the attributes of robots, it is not likely for Robot Cloud to share the same system architecture as traditional cloud computing without any change. We present the novel Robot Cloud architecture in Section  3, partly learning from the cloud computing architecture.

The rest of the paper is organized as follows. Section  2 introduces related work that supports the design of our system. Section  3 proposes the overall design of the Robot Cloud architecture that characterizes a Cloud framework containing robot resources. Section  4 presents in detail the most important features of the Robot Cloud architecture, i.e., how to achieve the Robot as a Service (RaaS). The feasibility studies on the Robot Cloud are shown in Section  5, where we develop a prototype using the popular Google App Engine platform  [4] to testify our idea. The first application of the Robot Cloud that comes to our minds is the “robot show”, which could be exemplified as a scenario of on-site service providing. We conduct the simulation to evaluate our scheduling algorithm, the effect of different request distributions and the advantage of one large robot center, which is elaborated in Section  6. The conclusion is presented in Section  7.

Section snippets

Service-Oriented Architecture

Service-Oriented Architecture (SOA)  [2] is not a revolutionary shift of paradigm. It evolves from the distributed object  [5] and component architecture  [6]. In an SOA environment, end users request an IT service (or an integrated collection of such services) at the desired function, quality, and capacity level, and receive it either at the time as it is requested or at a later time specified by the users. Service discovery, interoperability, and reliability are important functionalities that

Robot as a service

As SOA becomes more and more popular, this new architecture style has been applied to the development of robotics application. Chen applied the SOA concepts to develop re-composable embedded systems and robotics applications, and implemented a prototype of the system  [36]. Researchers encapsulate the functions of every part of robot and the robotics applications as well-defined services. Programmers are then able to assemble new robotics applications using these services. In this way, the

Target business model

A good understanding of the target business model greatly helps us design the architecture of the Robot Cloud. Generally, there are four parties in the target business model of Robot Cloud, which are Robot Cloud Service Provider, Cloud Computing /Robotics Provider, Value-added Service Provider, and also the Consumer. The relationship among all the roles can be illustrated by Fig. 2.

The Robot Cloud is owned by the Robot Cloud Service Provider, who is responsible for the management, government,

The cloud robot prototype

A robot is a good combination of the digital cyber world and the real world. Most of the robots controlling programs are written in object oriented languages such as Java and C++. The libraries that most robot manufacturer used to program the robot actions are similar. With these libraries, it is easy for the users to develop their own controlling algorithms and make the robots perform desired actions.

We have implemented a prototype of the robot cloud based on the infrastructure and components

Simulation model and setup

In this section we consider a simple scenario that a robot center can only provide one service, “robot show”, for a given physical area. The families or organizations (such as kindergartens) can request the robot center at certain time to play the on-site robot show at any location of the given area. The customers will be charged only based on the service time. The longer the show is, more fee will be charged.

The customer’s request is formulated as a 4-tuple req=R,P,S,D, where R is the

Conclusion and future work

We have developed a way of building a Robot Cloud in order to combine the cyber (virtual) world and the physical world. The Robot Cloud has the great potential to serve the diverse and large amount of location-based on-site demands, which cannot be handled by the existing cloud systems.

The prototype implemented in this work and the simulation results show that (1) the virtualization of robot resources is feasible, (2) the virtualization can improve the profit of the robot center, and (3) one

Acknowledgments

This research is supported in part by National Natural Science Foundation of China ​(Nos. 61440057, 61272087, 61363019 and 61073008), Beijing Natural Science Foundation ​(Nos. 4082016 and 4122039), the Sci-Tech Interdisciplinary Innovation and Cooperation Team Program of the Chinese Academy of Sciences, the Specialized Research Fund for State Key Laboratories.

Zhihui Du received the B.E. degree from the Computer Department, Tianjin University, in 1992, and the M.S. and Ph.D. degrees in computer science from Peking University, in 1995 and 1998, respectively. From 1998 to 2000, he worked at Tsinghua University as a postdoctoral researcher. Since 2001, he has been an associate professor at the Department of Computer Science and Technology, Tsinghua University. His research interests include high performance computing and grid computing. He is a member

References (42)

  • L. He et al.

    Developing resource consolidation frameworks for moldable virtual machines in clouds

    Future Gener. Comput. Syst.

    (2014)
  • Michael Armbrust et al.

    A view of cloud computing

    Commun. ACM

    (2010)
  • Thomas Erl

    Service-oriented Architecture: Concepts, Technology, and Design

    (2005)
  • J. Kuffner, Cloud enabled humanoid robots, Humanoids 2010 Workshop Talks,...
  • Google Inc. Google apps engine....
  • K. Ostrowski et al.

    Programming with live distributed objects

  • Rob Armstrong et al.

    Toward a common component architecture for high-performance scientific computing

  • Vlad M. Trifa, Christopher M. Cianci, Dominique Guinard, Dynamic control of a robotic swarm using a serviced-oriented...
  • Yinong Chen, S. Abhyankar, L. Xu, W.T. Tsai, Marcos Garcia-Acosta: Developing a security robot in service-oriented...
  • Amazon Web Services. Amazon web services homepage....
  • K. Lai et al.

    Tycoon: an implementation of a distributed market-based resource allocation system

    Multiagent Grid Syst.

    (2005)
  • Hewlett-Packard, HP Integrated Lights-Out 2 User Guide, Technical Report, HP,...
  • Sanjay Ghemawat, Howard Gobioff, Shun-Tak Leung, The Google file system, in: ACM Symposium on Operating Systems...
  • N. McKeown, T. Anderson, H. Balakrishnan, G. Parulkar, L. Peterson, J. Rexford, S. Shenker, J. Turner, Openflow:...
  • Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Mike Burrows, Tushar Chandra, Andrew...
  • PaaS....
  • S. Microsystems, Project caroline....
  • Microsoft, Azure Services Platform....
  • M.H. Weier et al.

    Businesses get serious about software as a service

    Informat. Week

    (2007)
  • Google Inc. Google docs....
  • P.A. Laplante et al.

    What’s in a name? Distinguishing between SaaS and SOA

    IT Prof.

    (2008)
  • Cited by (0)

    Zhihui Du received the B.E. degree from the Computer Department, Tianjin University, in 1992, and the M.S. and Ph.D. degrees in computer science from Peking University, in 1995 and 1998, respectively. From 1998 to 2000, he worked at Tsinghua University as a postdoctoral researcher. Since 2001, he has been an associate professor at the Department of Computer Science and Technology, Tsinghua University. His research interests include high performance computing and grid computing. He is a member of the IEEE.

    Ligang He is an associate professor of University of Warwick. His research interests include Cloud Computing, Grid Computing, Cluster Computing, Parallel and Distributed Processing, High Performance Computing, Performance Modeling and Evaluation, Real-time Processing. He has served for many conferences and journals. He has published many top level journal and conference papers.

    Yinong Chen is a Senior Lecturer of Arizona State University. He got his Ph.D. degree from University of Karlsruhe/KIT, Germany. He has published more than 100 conferences and journal papers. He is the Area Editor of the Elsevier Journal: Simulation Modeling Practice and Theory, since Jan 2006 and Associate Editor of the International Journal of Simulation and Process Modelling (IJSPM), since Jan. 2004.

    View full text