• DocumentCode
    172970
  • Title

    A Software Product Line Approach for Configuring Cloud Robotics Applications

  • Author

    Gherardi, L. ; Hunziker, D. ; Mohanarajah, G.

  • Author_Institution
    Inst. for Dynamic Syst. & Control, ETH Zurich, Zurich, Switzerland
  • fYear
    2014
  • fDate
    June 27 2014-July 2 2014
  • Firstpage
    745
  • Lastpage
    752
  • Abstract
    The computational requirements of the increasingly sophisticated algorithms used in today´s robotics software applications have outpaced the onboard processors of the average robot. Furthermore, the development and configuration of these applications are difficult tasks that require expertise in diverse domains, including software engineering, control engineering, and computer vision. As a solution to these problems, this paper extends and integrates our previous works, which are based on two promising techniques: Cloud Robotics and Software Product Lines. Cloud Robotics provides a powerful and scalable environment to offload the computationally expensive algorithms resulting in low-cost processors and light-weight robots. Software Product Lines allow the end user to deploy and configure complex robotics applications without dealing with low-level problems such as configuring algorithms and designing architectures. This paper discusses the proposed method in depth, and demonstrates its advantages with a case study.
  • Keywords
    cloud computing; control engineering; intelligent robots; robot vision; software product lines; cloud computing; cloud robotics; computer vision; control engineering; light-weight robots; onboard processors; robotic software applications; software engineering; software product line approach; sophisticated algorithms; Cloud computing; Computational modeling; Computer architecture; Containers; Robots; Software as a service; Cloud Computing; Robotics; Software Product Lines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing (CLOUD), 2014 IEEE 7th International Conference on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    978-1-4799-5062-1
  • Type

    conf

  • DOI
    10.1109/CLOUD.2014.104
  • Filename
    6973810