  In general, optimal motion planning can be performed both locally and
globally. In such a planning, the choice in favour of either local or global
planning technique mainly depends on whether the environmental conditions are
dynamic or static. Hence, the most adequate choice is to use local planning or
local planning alongside global planning. When designing optimal motion
planning both local and global, the key metrics to bear in mind are execution
time, asymptotic optimality, and quick reaction to dynamic obstacles. Such
planning approaches can address the aforesaid target metrics more efficiently
compared to other approaches such as path planning followed by smoothing. Thus,
the foremost objective of this study is to analyse related literature in order
to understand how the motion planning, especially trajectory planning, problem
is formulated, when being applied for generating optimal trajectories in
real-time for Multirotor Aerial Vehicles (MAVs), impacts the listed metrics. As
a result of the research, the trajectory planning problem was broken down into
a set of subproblems, and the lists of methods for addressing each of the
problems were identified and described in detail. Subsequently, the most
prominent results from 2010 to 2022 were summarized and presented in the form
of a timeline.
