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. TheNote to Practitioners The work described in this article is part of the EU funded RoboEarth project, in which knowledge repositories and intelligent services are developed to operate service robots world wide. The centralized task controller described here can be regarded as one of these intelligent services, that realizes a time-optimal allocation of multiple robots. This work shows significant similarities with the (not publicly available) ubiquitous task controller designed by Ha, where our work uses a more expressive action language. The general use of our system from a human end-user point of view is to request for a list of tasks, for which an abstract plan and according parameterizations are selected by the system. The selected plan is subsequently parsed into a Golog based planning interpreter, that binds available robots and all the other parameters (such as objects and locations). The parametrized actions involved in the plan are mapped onto computational algorithms and robots in a time-optimal manner, and subsequently executed by interfacing with them through a service(http)-based interface. What should be noted is that the executing robots themselves serve merely as sensor-actuator platforms, leaving all the computations to be performed on the Cloud. Our opinion is that this deployment advances the opportunity for calculation optimization and the instant reuse of updated task knowledge, e.g. object locations, action plans, and robot capabilities on a global level. 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 impo...
