  Edge Computing is a promising technology to provide new capabilities in
technological fields that require instantaneous data processing. Researchers in
areas such as machine and deep learning use extensively edge and cloud
computing for their applications, mainly due to the significant computational
and storage resources that they provide. Currently, Robotics is seeking to take
advantage of these capabilities as well, and with the development of 5G
networks, some existing limitations in the field can be overcome. In this
context, it is important to know how to utilize the emerging edge
architectures, what types of edge architectures and platforms exist today and
which of them can and should be used based on each robotic application. In
general, Edge platforms can be implemented and used differently, especially
since there are several providers offering more or less the same set of
services with some essential differences. Thus, this study addresses these
discussions for those who work in the development of the next generation
robotic systems and will help to understand the advantages and disadvantages of
each edge computing architecture in order to choose wisely the right one for
each application.
