Correlated Orienteering Problem and its application to informative path planning for persistent monitoring tasks

We propose a novel non-linear extension to the Orienteering Problem (OP), called the Correlated Orienteering Problem (COP). We use COP to plan informative tours (cyclic paths) for persistent monitoring of an environment with spatial correlations, where the tours are constrained to a fixed length or time budget. The main feature of COP is a quadratic utility function that captures spatial correlations among points of interest that are close to each other. COP may be solved using mixed integer quadratic programming (MIQP) that can plan multiple disjoint tours that maximize the quadratic utility function. We perform extensive characterization of our method to verify its correctness, as well as its applicability to the estimation of a realistic, time-varying, and spatially correlated scalar field.

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