# Networking for Cloud Robotics: The DewROS Platform and Its Application
## 3 DewROS: Our Dew Robotics Platform  
The unstoppable proliferation of IoT devices and the rapid progress in robotics and networking technologies has led to the evolution of the Cloud Robotics paradigm towards more flexible models, namely, Fog and Dew Robotics [2]. They promote smarter use of all the systems, such as end, edge and cloud devices, involved in the provision of a service, to meet the different application requirements. Cloud robotics proposes moving robot brains in the Cloud to make them perform better, act smarter, and learn faster. Robots can access a shared pool of potentially unlimited cloud resources through a network connection, which moves data between them and remote servers. On the other hand, a fault in or a temporary lack of availability of the network might compromise the execution of a crucial task; for example, obstacles and interference can limit the range and the strength of a wireless network signal. Moreover, a network with sudden latency spikes might lead to failure in a real-time task. Therefore, not all robotic tasks are meant to be offloaded to the Cloud, but some of them need different application requirements to be completed. For instance, the aerial vehicles of the SHERPA team can cover significant distances, so they can temporarily leave the wireless network range and no longer communicate with the other units of the robotic platform, including the ground rover, used as a bridge to the Cloud. The drones of the SHERPA team must be able to detect a collision with the environmental elements with no network coverage, running a local algorithm, and relying on their onboard resources. Any task requiring short reaction times should be not delegated to the Cloud, because the unpredictable behavior of the network might lead to its failure. The key concept of Fog Computing and, therefore, of Fog Robotics, is to extend the Cloud paradigm by ensuring that a subset of the requested remote service is available when it is closer to the end-user, e.g., in the edge network devices. This model involves the design of large-scale distributed applications and systems, in which the proximity of fog nodes, with their greater storage and computation abilities and lower power consumption constraints, represents a crucial factor for the reduction in network latency. The closer the stored data and computations are to the end-user, the smaller the response time. For instance, the ground rover of the SHERPA team plays the role of a Fog node, which \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Platform**} & \multirow{2}{*}{**ROS-Enabled**} & **Cloud** & **Edge** & **Video** & **Experimental** & **Search** \\  & & **Support** & **Support** & **Processing** & **Validation** & **and Rescue** \\ \hline [PERSON] et al. [17] & ✓ & ✓ & ✗ & ✓ & ✓ & ✗ \\ \hline [PERSON] et al. [18] & ✗ & ✓ & ✓ & ✗ & ✓ & ✗ \\ \hline [PERSON] et al. [19] & ✓ & ✓ & ✓ & ✗ & ✗ & ✗ \\ \hline [PERSON] et al. [20] & ✗ & ✓ & ✗ & ✗ & ✓ & ✗ \\ \hline [PERSON] et al. [21] & ✓ & ✗ & ✗ & ✗ & ✓ & ✗ \\ \hline [PERSON] et al. [22] & ✓ & ✓ & ✗ & ✓ & ✓ & ✗ \\ \hline [PERSON] et al. [23] & ✓ & ✓ & ✗ & ✗ & ✓ & ✗ \\ \hline [PERSON] et al. [29] & ✓ & ✓ & ✗ & ✓ & ✓ & ✗ \\ \hline [PERSON] et al. [24] & ✓ & ✗ & ✗ & ✗ & ✗ & ✓ \\ \hline [PERSON] et al. [25] & ✗ & ✗ & ✓ & ✗ & ✗ & ✓ \\ \hline [PERSON] et al. [26] & ✗ & ✗ & ✓ & ✗ & ✗ & ✓ \\ \hline [PERSON] et al. [27] & ✓ & ✗ & ✓ & ✗ & ✗ & ✓ \\ \hline [PERSON] et al. [28] & ✓ & ✗ & ✓ & ✗ & ✗ & ✓ \\ \hline [PERSON] [31] & ✗ & ✗ & ✓ & ✗ & ✓ & ✗ \\ \hline DewROS & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparing DewROS with related work. can temporarily store the massive amount of visual data captured by the drones before processing or support some of their tasks, such as route re-planning after a collision is avoided. However, a reliable network connection is still needed, at least until the Fog nodes, to use their services. The other key factors considered in this work are system reliability and resilience.