Recently, unmanned vehicles have attracted a great deal of attention
in academic, civilian and military communities as prospective
solutions to a wide variety of applications. With this growing
interest, there has been a great development of unmanned systems
control techniques. One of the promising approaches in the field of
unmanned systems is model predictive control (MPC) due to its
ability to handle the multi-variable constrained systems. Therefore,
the goal of this paper is to present a comprehensive literature of
applying MPC for motion control of both unmanned ground
vehicles (UGVs) and unmanned aerial vehicles (UAVs). First, an
overview of motion control principles is presented. Next, an
overview of MPC including its concept, formulation, types, and its
stability is provided. Then, a comprehensive literature review of
applying MPC to both UGVs and UAVs is introduced, including the
basic motion tasks such as path planning, point stabilization, and
trajectory tracking. Finally, open problems, challenges, and future
directions are highlighted.