  Terrestrial robots, i.e., unmanned ground vehicles (UGVs), and aerial robots,
i.e., unmanned aerial vehicles (UAVs), operate in separate spaces. To exploit
their complementary features (e.g., fields of views, communication links,
computing capabilities), a promising paradigm termed integrated robotics
network emerges, which provides communications for cooperative UAVs-UGVs
applications. However, how to efficiently deploy UAVs and schedule the
UAVs-UGVs connections according to different UGV tasks become challenging. In
this paper, we propose a sum-rate maximization problem, where UGVs plan their
trajectories autonomously and are dynamically associated with UAVs according to
their planned trajectories. Although the problem is a NP-hard mixed integer
program, a fast polynomial time algorithm using alternating gradient descent
and penalty-based binary relaxation, is devised. Simulation results demonstrate
the effectiveness of the proposed algorithm.
