Planning Visual Inspection Tours for a 3D Dubins Airplane Model in an Urban Environment

TL;DR

This paper develops a method for planning minimal-length inspection tours for a 3D Dubins airplane in urban environments, incorporating visibility constraints and efficient sampling and heuristic algorithms.

Contribution

It extends the DTSPN to three dimensions with visibility volumes and introduces sampling algorithms and heuristics for efficient tour planning.

Findings

Proposed sampling algorithms effectively generate feasible viewing configurations.

Heuristic approach reduces computation time significantly.

Method outperforms baseline in urban environment simulations.

Abstract

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.