Cooperative robotic healthcare systems (CRHS) are advanced technologies that enhance medical services by allowing robots to collaborate with healthcare professionals, making clinical practices safer and more efficient. However, for these systems to work efficiently, they need fast and reliable communication and computation, all while managing the limited resources and energy available in robot-embedded sensors. Therefore, this survey focuses on clarifying how various networking and computing decisions impact different aspects of this technology, such as latency, reliability, Quality of Service (QoS), and scalability, etc. We evaluated the recent research on resource allocation, as well as orchestration in edge, fog, and cloud computing, to have a holistic overview of what has been done so far in this field. Moreover, we analyzed communication technologies such as 5G, Ultra-Reliable Low-Latency Communication (URLLC), Time-Sensitive Networking (TSN), Software-Defined Networking (SDN), Network Function Virtualization (NFV), and network slicing to understand their role in RHCS QoS metrics. Our synthesis finds that (i) placing perception/control close to the edge consistently decreases end-to-end delay, (ii) SDN/NFV and time-sensitive networking improve predictable and real-time operation in multi-robot hospital environments; and (iii) learning-based scheduling and offloading often outperform static heuristics in variable workloads. Despite these advancements, we have identified several challenges in the literature, such as limited interoperability between different vendors and a lack of standardized benchmarks for Quality of Service (QoS), etc. Therefore, we conducted a comparative analysis to understand how specific design choices influence the QoS metrics of this technology. In addition, we have proposed potential research directions that address the open challenges to ensure the real deployment of this technology.
Adil et al. (Mon,) studied this question.