  Within this paper, the problem of 3D structural inspection path planning for
distributed infrastructure using aerial robots that are subject to time
constraints is addressed. The proposed algorithm handles varying spatial
properties of the infrastructure facilities, accounts for their different
importance and exploration function and computes an overall inspection path of
high inspection reward while respecting the robot endurance or mission time
constraints as well as the vehicle dynamics and sensor limitations. To achieve
its goal, it employs an iterative, 3-step optimization strategy at each
iteration of which it first randomly samples a set of possible structures to
visit, subsequently solves the derived traveling salesman problem and computes
the travel costs, while finally it samples and assigns inspection times to each
structure and evaluates the total inspection reward. For the derivation of the
inspection paths per each independent facility, it interfaces a path planner
dedicated to the 3D coverage of single structures. The resulting algorithm
properties, computational performance and path quality are evaluated using
simulation studies as well as experimental test-cases employing a multirotor
micro aerial vehicle.
