  Planning the path to gather the surface information of the target objects is
crucial to improve the efficiency of and reduce the overall cost, for visual
inspection applications with Unmanned Aerial Vehicles (UAVs). Coverage Path
Planning (CPP) problem is often formulated for these inspection applications
because of the coverage requirement. Traditionally, researchers usually plan
and optimize the viewpoints to capture the surface information first, and then
optimize the path to visit the selected viewpoints. In this paper, we propose a
novel planning method to directly sample and plan the inspection path for a
camera-equipped UAV to acquire visual and geometric information of the target
structures as a video stream setting in complex 3D environment. The proposed
planning method first generates via-points and path primitives around the
target object by using sampling methods based on voxel dilation and
subtraction. A novel Primitive Coverage Graph (PCG) is then proposed to encode
the topological information, flying distances, and visibility information, with
the sampled via-points and path primitives. Finally graph search is performed
to find the resultant path in the PCG to complete the inspection task with the
coverage requirements. The effectiveness of the proposed method is demonstrated
through simulation and field tests in this paper.
