  Due to their ability to anchor into tall urban landforms, such as lampposts
or street lights, robotic aerial base stations (RABSs) can create a
hyper-flexible wireless multi-hop heterogeneous network to meet the forthcoming
green, densified, and dynamic network deployment to support, inter alia, high
data rates. In this work, we propose a network infrastructure that can
concurrently support the wireless backhaul link capacity and access link
traffic demand in the millimeter-wave (mmWave) frequency band. The RABSs
grasping locations, resource blocks (RBs) assignment, and route flow control
are simultaneously optimized to maximize the served traffic demands. Robotic
base stations capitalize on the fact that traffic distribution varies
considerably across both time and space within a given geographical area.
Hence, they are able to relocate to suitable locations, i.e., 'follow' the
traffic demand as it unfolds to increase the overall network efficiency. To
tackle the curse of dimensionality of the proposed mixed-integer linear
problem, we propose a greedy algorithm to obtain a competitive solution with
low computational complexity. Compared to baseline models, which are
heterogeneous networks with randomly deployed fixed small cells and
pre-allocated RBs for wireless access and backhaul links, a wide set of
numerical investigations reveals that robotic base stations could improve the
served traffic demand. Specifically, the proposed mode serves at most 65\% more
traffic demand compared to an equal number of deployed fixed small cells.
