  In this paper, we consider the problem of generating inspection paths for
robots. These paths should allow an attached measurement device to perform
high-quality measurements. We formally show that generating robot paths, while
maximizing the inspection quality, naturally corresponds to the submodular
orienteering problem. Traditional methods that are able to generate solutions
with mathematical guarantees do not scale to real-world problems. In this work,
we propose a method that is able to generate near-optimal solutions for
real-world complex problems. We experimentally test this method in a wide
variety of inspection problems and show that it nearly always outperforms
traditional methods. We furthermore show that the near-optimality of our
approach makes it more robust to changing the inspection problem, and is thus
more general.
