Robotic systems are more connected, networked, and distributed than ever. New
architectures that comply with the \textit{de facto} robotics middleware
standard, ROS\,2, have recently emerged to fill the gap in terms of hybrid
systems deployed from edge to cloud. This paper reviews new architectures and
technologies that enable containerized robotic applications to seamlessly run
at the edge or in the cloud. We also overview systems that include solutions
from extension to ROS\,2 tooling to the integration of Kubernetes and ROS\,2.
Another important trend is robot learning, and how new simulators and cloud
simulations are enabling, e.g., large-scale reinforcement learning or
distributed federated learning solutions. This has also enabled deeper
integration of continuous interaction and continuous deployment (CI/CD)
pipelines for robotic systems development, going beyond standard software unit
tests with simulated tests to build and validate code automatically. We discuss
the current technology readiness and list the potential new application
scenarios that are becoming available. Finally, we discuss the current
challenges in distributed robotic systems and list open research questions in
the field