The Generalized Persistent Monitoring Problem Conference Paper uri icon


  • 2019 American Automatic Control Council. In this article, we consider the problem of planning an optimal route for an unmanned vehicle, tasked with persistently monitoring a set of targets. The targets are grouped into m subsets, referred to as clusters. To monitor a cluster, the vehicle must collect data from any one target in the cluster, by making a physical visit to the target. The vehicle has a finite fuel capacity, which is specified in terms of the number of visits it can make, at the end of which it must be refueled/recharged at a depot (which is one of the targets). Given k allowed visits for the vehicle, the problem of interest is to plan a closed walk (route) of k visits that can be repeated continuously, such that the maximum time between successive visits to the clusters is minimized (the minimum value is mathcal{R}-{ast}(k)). Here, we prove that for kgeq m-{2}-m, mathcal{R}-{ast}(k) takes only two values, mathcal{R}-{ast}(m) when k is an integral multiple of m, and mathcal{R}-{ast}(m+1) otherwise, leading to significant computational savings. We corroborate this result by performing numerical simulations on a Dubins vehicle.

name of conference

  • 2019 American Control Conference (ACC)

published proceedings


author list (cited authors)

  • Hari, S., Rathinam, S., Darbha, S., Kalyanam, K., Manyam, S. G., & Casbeer, D.

citation count

  • 13

complete list of authors

  • Hari, SKK||Rathinam, S||Darbha, S||Kalyanam, K||Manyam, SG||Casbeer, D

publication date

  • August 2019