This paper investigates the problem of planning a minimum-length tour for a
three-dimensional Dubins airplane model to visually inspect a series of targets
located on the ground or exterior surface of objects in an urban environment.
Objects are 2.5D extruded polygons representing buildings or other structures.
A visibility volume defines the set of admissible (occlusion-free) viewing
locations for each target that satisfy feasible airspace and imaging
constraints. The Dubins traveling salesperson problem with neighborhoods
(DTSPN) is extended to three dimensions with visibility volumes that are
approximated by triangular meshes. Four sampling algorithms are proposed for
sampling vehicle configurations within each visibility volume to define
vertices of the underlying DTSPN. Additionally, a heuristic approach is
proposed to improve computation time by approximating edge costs of the 3D
Dubins airplane with a lower bound that is used to solve for a sequence of
viewing locations. The viewing locations are then assigned pitch and heading
angles based on their relative geometry. The proposed sampling methods and
heuristics are compared through a Monte-Carlo experiment that simulates view
planning tours over a realistic urban environment.Comment: 18 pages, 10 figures, Presented at 2023 SciTech Intelligent Systems
in Guidance Navigation and Control conferenc