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Rapyuta: A Cloud Robotics Platform
Automation Science and Engineering, IEEE Transactions , no. 2 (2015): 481-493
- T HE past decade has seen the first successful, large-scale use of mobile robots. the vast majority of these robots either continue to use simple control strategies (e.g., robot vacuum cleaners) or are operated remotely by humans (e.g., drones, unmanned ground vehicles, and telepresence robots).
- The vast majority of these robots either continue to use simple control strategies or are operated remotely by humans
- One reason these mobile robots lack intelligence is because the costs of onboard computation and storage are high; this affects the robot's price point, and results in the need for additional space and extra weight, which constrain the robot's mobility and operation time.
- Cloud robotics applications hold the potential for lighter, smarter, and more cost-effective robots
- T HE past decade has seen the first successful, large-scale use of mobile robots
- We described the design, implementation, benchmarking results, and the first demonstrations of Rapyuta, a PaaS framework for robots
- We showed how the computing environments and the communication protocols allow robots to offload their computation to the cloud
- We described how Rapyuta's computing environments can be interconnected to share specific resources with other environments, making it a suitable framework for multi-robot control and coordination
- Our choice of communication protocols were explained, and an example was provided to clarify the different types of messages and to show how they work together
- We provided some benchmarking results for different protocols
- The authors described the design, implementation, benchmarking results, and the first demonstrations of Rapyuta, a PaaS framework for robots.
- Rapyuta, based on an elastic computing model, dynamically allocates secured computing environments for robots.
- The authors showed how the computing environments and the communication protocols allow robots to offload their computation to the cloud.
- The authors provided some benchmarking results for different protocols
- This work was supported by the European Union Seventh Framework Programme FP7/2007–2013 under Grant 248942 RoboEarth and by AWS (Amazon Web Services) in Education Grant Award
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- Dominique Hunziker received the B.S. degree in mechanical engineering from ETH Zurich, Zurich, Switzerland, in 2011, where he is currently working toward the M.S. degree.
- Raffaello D'Andrea received the B.Sc. degree in engineering science from the University of Toronto, Toronto, ON, Canada, in 1991, and the M.S. and Ph.D. degrees in electrical engineering from the California Institute of Technology, Pasadena, CA, USA, in 1992 and 1997, respectively.
- He held positions as an Assistant Professor and later an Associate Professor with Cornell University, Ithaca, NY, USA, from 1997 to 2007. He is currently a Full Professor of dynamic systems and control with ETH Zurich, Zurich, Switzerland, and Technical Cofounder and Chief Technical Advisor with Kiva Systems.
- Markus Waibel received the M.Sc. degree in physics from the Technical University of Vienna, Vienna, Austria, in 2003, and the Ph.D. degree in robotics from the EPF Lausanne, Lausanne, Switzerland, in 2007.
- He is currently a Senior Researcher with ETH Zurich, Zurich, Switzerland, and Program Manager of the cloud robotics project RoboEarth. He is also the Cofounder of the ROBOTS Association and its flagship publications Robohub and the ROBOTS Podcast, and the founder of Robotics by Invitation, an online panel discussion of 30 high-profile roboticists.