  In recent years, using drone, also known as unmanned aerial vehicle (UAV), in
close-distance visual inspection has became an active area in many disciplines.
However, many challenges still remain before we can achieve autonomous
inspection, especially when inspecting complex structures. The complex civil
structures, such as bridges, dams and wind turbines, are large-scale and
geometrical complicated. It requires sophisticated path planning algorithms to
achieve close-distance inspection and, at the same time, avoid collisions. In
practice, directly deploying the path planning result on such structures is
error prone, costly, and full of hazards. In this paper, rely on micro
quadrotor UAV, the authors present an affordable experimental platform for
testing drone-based path planning result. The platform allows the users to
conduct many path planning experiments at any time without worrying expensive
and time consuming outdoor test flying. This platform is developed based on the
bundle of Crazyflie, which includes Crazyflie 2.0 quadrotor, Crazyradio and
loco positioning system (LPS). Equipped with an onboard micro FPV camera, the
visual data can be lively streamed to the host computer during flight. The
functions of manual configuration and waypoints control are explicitly designed
in this platform to increase its flexibility and performance on path following
and debugging. To evaluate the practicability of the proposed test platform,
two existing drone-based path planning algorithms are tested. The results show
that even though certain level of error existed, the quality of visual data and
accuracy of path following are high enough for simulating most practical
inspection applications.
