Cloud based centralized task control for human domain multi-robot operations

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With an increasing number of assistive robots operating in human domains, research efforts are being made to design control systems that optimize the efficiency of multi-robot operations. As part of the EU funded RoboEarth project, this paper discusses the design of such a system, where a variety of existing components are selected and combined into one cohesive control architecture. The architecture’s main design principle stems from Radestock’s ‘separation of concerns’, which dictates the separation of software architectures into four disjunct components; coordination, configuration, communication and computation. For the system’s coordinating component a Golog based planning layer is integrated with a custom made execution module. Here, the planning layer selects and parametrizes abstract action plans, where the execution layer subsequently grounds and executes the involved actions. Plans and plan related context are represented in the OWL-DL logics representation, which allows engineers to model plans and their context using first-order logic principles and accompanying design tools. The communication component is established through the RoboEarth Cloud Engine, enabling global system accessibility, secure data transmissions and the deployment of heavy computations in a Cloud based computing environment. We desire these computations, such as kinematics, motion planning and perception, to all run on the Cloud Engine, allowing robots to remain lightweight, the instant sharing of data between robots and other algorithms and most importantly, the reuse of these algorithms for a variety of multi-robot operations. A first design of the system has been implemented and evaluated for its strengths and weaknesses through a basic, but fundamental real-world experiment.
Original languageEnglish
Pages (from-to)63-77
Number of pages15
JournalIntelligent Service Robotics
Issue number1
Publication statusPublished - 1 Jan 2016


  • Centralized control
  • Cloud computing
  • Knowledge engineering
  • Service robots


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