Rapyuta: The RoboEarth Cloud Engine

Hunziker, Dominique; Mohanarajah, Gajamohan; Waibel, Markus; D’Andrea, Raffaello

doi:10.1109/icra.2013.6630612

Cited by 142 publications

(72 citation statements)

References 13 publications

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“…Recently, CORE has utilized the SaaS for a distributed and scalable cloud-enabled architecture for object recognition [20]. Alternatively, Platform-as-a-Service (PaaS) is a model used by Rapyuta [21] for applications like RoboEarth that uses cloud for robot knowledge sharing. In our work, we use PaaS to access the available software platform and build on that.…”

Section: Current Trendsmentioning

confidence: 99%

Cloud-Enhanced Robotic System for Smart City Crowd Control

Rahman

Jin

Cricenti

et al. 2016

JSAN

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Cloud robotics in smart cities is an emerging paradigm that enables autonomous robotic agents to communicate and collaborate with a cloud computing infrastructure. It complements the Internet of Things (IoT) by creating an expanded network where robots offload data-intensive computation to the ubiquitous cloud to ensure quality of service (QoS). However, offloading for robots is significantly complex due to their unique characteristics of mobility, skill-learning, data collection, and decision-making capabilities. In this paper, a generic cloud robotics framework is proposed to realize smart city vision while taking into consideration its various complexities. Specifically, we present an integrated framework for a crowd control system where cloud-enhanced robots are deployed to perform necessary tasks. The task offloading is formulated as a constrained optimization problem capable of handling any task flow that can be characterized by a Direct Acyclic Graph (DAG). We consider two scenarios of minimizing energy and time, respectively, and develop a genetic algorithm (GA)-based approach to identify the optimal task offloading decisions. The performance comparison with two benchmarks shows that our GA scheme achieves desired energy and time performance. We also show the adaptability of our algorithm by varying the values for bandwidth and movement. The results suggest their impact on offloading. Finally, we present a multi-task flow optimal path sequence problem that highlights how the robot can plan its task completion via movements that expend the minimum energy. This integrates path planning with offloading for robotics. To the best of our knowledge, this is the first attempt to evaluate cloud-based task offloading for a smart city crowd control system.

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Section: Current Trendsmentioning

confidence: 99%

Cloud-Enhanced Robotic System for Smart City Crowd Control

Rahman

Jin

Cricenti

et al. 2016

JSAN

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“…A secure, ROS based communication framework that is publicly available, is the RoboEarth Cloud Engine, or Rapyuta [31]. Rapyuta is a well-documented communication framework, and is developed as part of the effort for global communication and knowledge reuse in the RoboEarth project [61].…”

Section: Communication Frameworkmentioning

confidence: 99%

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

Janssen

Molengraft

Bruyninckx

et al. 2015

Intel Serv Robotics

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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. 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...

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“…Such information can be used by a robot (and its hardware) to extend a robots sensing, reasoning and functionality. Rapyuta [2] [3] is an open-source cloud computing component that creates a Platform-as-a-Service (PaaS) framework to move computational intensive activities from robots into the cloud. Each robot running Rapyuta creates a virtual container in the cloud that can be used to store data, to run computational intensive tasks, exchange information with other Rapyuta containers, and connect to the RoboEarth knowledge database [5].…”

Section: Roboearth Platformmentioning

confidence: 99%