A randomized art-gallery algorithm for sensor placement

This paper descirbes a placement strategy to compute a set of “good” locations where visual sensing will be most effective. Throughout this paper it is assumed that a {\em polygonal 2-D map} of a workspace is given as input. This polygonal map --- also known as a {\em floor plan} of {\em layout} --- is used to compute a set of locations where expensive sensing tasks (such as 3-D image acquisition) could be executed. A map-building robot, for example, can visit these locations in order to build a full 3-D model of the workspace.

The sensor placement strategy relies on a randomized algorithm that solves a variant of the {\em art-gallery problem}-\cite{Oro87, She92, Urr97} : Find the minimum set of guards inside a polygonal workspace from which the entire workspace boundary is visibe. To better take into account the limitations of physical sensors, the algorithm computes a set of guards that satisfies incidence and range constraints. Although the computed set of guards is not guaranteed to have minimum size, the algorithm does compute with high probability a set whose size is at most a factor $\big0{ (n + h) \cot \log(c \ (n + h) )$ from the optimal size$c$, where $n$ is the number of edges in the input polygonal map and $n$ the number of obstacles in its interior (holes).