With “Cloud Computing” becoming more and more popular, there has been increasing interest in applying similar concepts to robotics: Performing complex computations or storing large-scale knowledge bases can often be done more efficiently on dedicated server hardware, requiring less computing power, less memory and therefore also less battery capacity on the robot itself. Applications of these concepts to robotics are commonly referred to as “cloud robotics” [1]. There have been several efforts to move parts of the robot control program into the cloud, each focusing on different aspects like storing and sharing knowledge, off-loading complex computations, coordinating distributed robot teams, or remotely operating partly autonomous robots. Kamei et al. [2] introduce the Ubiquitous Networked Robot Platform (UNR-PF) as a framework for distributed task coordination and control. The UNR-PF abstracts away from the robot’s concrete hardware and offers a generic interface that can be used by application developers to create hardware-independent robotic services. A developer can request components that fulfill a given specification, and the UNR-PF will then assign suitable devices that can be controlled remotely. The UNR-PF supports a hierarchy of local and global platforms that allow to remotely start, supervise and coordinate tasks that are jointly performed by a set of components on different physical robots. Taken together, the hardware abstraction and the networked control