# The Cloud-to-Edge-to-IoT Continuum as an Enabler for Search and Rescue Operations
## 2 Related Work
### Cloud and Edge Robotics for SAR  
The idea of utilizing a \"remote brain\" for robots can be traced back to the 90s [7; 8]. Since then, attempts to adopt cloud technologies in the robotics field have seen a constantly growing momentum. The benefits deriving from the integration of networked robots and cloud computing are, among others, powerful computation, storage, and communication resources available in the cloud which can support the information sharing and processing for robotic applications. The possibility of remotely controlling robotic systems further reduces costs for the deployment, monitoring, diagnostics, and orchestration of any robotic application. This, in turn, allows for building lightweight, low-cost, and smarter robots, as the main computation and communication burden is brought to the cloud. Since 2010, when the cloud robotics term first appeared, several projects (e.g., RoboEarth [9], KnowRob [10], DAVinci [11], Robobrain [12]) investigated the field, pushing forward both research and products to appear on the market. Companies started investing in the field as they recognized the large potential of cloud robotics. This led to the first open-source cloud robotics frameworks appearing in recent years [13]. An example of this is the solution from Ropyuta Robotics (Available online: [[https://www.rapyuta-robotics.com/](https://www.rapyuta-robotics.com/)]([https://www.rapyuta-robotics.com/](https://www.rapyuta-robotics.com/)) (accessed on 19 January 2023)). Similarly, commercial solutions for developers have seen the light such as Formant (Available online: [[https://formant.io/](https://formant.io/)]([https://formant.io/](https://formant.io/)) (accessed on 19 January 2023)), Robolaunch (Available online: [[https://www.robolaunch.io/](https://www.robolaunch.io/)]([https://www.robolaunch.io/](https://www.robolaunch.io/)) (accessed on 19 January 2023)) and Amazon's Robomaker [14]. Additionally, for key features such as navigation and localization in indoor environments, commercial products exist on the market. Adopting commercial solutions, however, leads to additional costs that might threaten the success of offering a low-cost product/service to the market. Open source offers customizable solutions with production and maintenance costs kept low, whereas ad hoc designed solutions allow us to deploy customized technology solutions in terms of services and features envisioned for the final product. With the advances in edge [15] and fog computing [16] in the last few years, robotics has seen an even greater potential as higher bandwidth and lower latencies can be achieved [17]. With computing and storage resources at the edge of the infrastructure, applications can be executed closer to the robotic hardware which generally improves the performance [17] and enables advanced applications that pure cloud-based robotics would not be able to support [18; 19; 20]. Multiple research and development (R&D) projects have investigated the adoption of robotic solutions in SAR operations. For instance, the SHERPA project [21] developed a mixed ground and aerial robotic platform with human-robot interaction to support search and rescue activities in real-world hostile environments; RESPOND-A [22] developed holistic solutions by bringing together 5G wireless communications, augmented and virtual reality, autonomous robot and unmanned aerial vehicle coordination, intelligent wearable sensors and smart monitoring, geovisual analytics and immersive geospatial data analysis, passive and active localization and tracking, and interactive multi-view 360-degrees video streaming. These are two examples of several projects that have investigated and demonstrated the use of robotic applications in SAR and disaster scenarios. Whereas the adoption of cloud and edge robotics for SAR has gained interest in recent years [20; 23; 24], how the cloud and edge computing frameworks can support SAR operations at their best is still an open challenge.