Showing papers by "Swaroop Darbha published in 2014"
27 May 2014
TL;DR: A novel GPS denied routing problem for UAVs is described, where two Uavs cooperatively navigate through an array of non-communicating Unattended Ground Sensors (UGS) to solve the Communication Constrained UAV Routing Problem (CCURP).
Abstract: A novel GPS denied routing problem for UAVs is described, where two UAVs cooperatively navigate through an array of non-communicating Unattended Ground Sensors (UGS). Contact with UGS is strictly maintained, which allows the UGS act as beacons for relative navigation eliminating the need for dead reckoning. This problem is referred to as the Communication Constrained UAV Routing Problem (CCURP). To solve the CCURP, shortest paths between targets are computed by means of a graph transformation. Given the shortest paths between targets, two solution methods are presented. The first is a 15 over 2-approximation algorithm. The second method poses the CCURP as an one-in-a-set Traveling Salesman Problem (TSP), which can then be solved using known methods by transforming the problem into a regular asymmetric TSP. Computational results corroborating the performance bounds in this article are also presented.
19 citations
TL;DR: In this article, a stochastic optimal control problem involving an unmanned aerial vehicle flying patrols around a perimeter is considered and the perimeter patrol problem exhibits a special structure that enables tractable linear programming formulation for the lower bound.
Abstract: In this article, a stochastic optimal control problem involving an unmanned aerial vehicle flying patrols around a perimeter is considered. To determine the optimal control policy, one has to solve a Markov decision problem, whose large size renders exact dynamic programming methods intractable. Therefore, a state aggregation based approximate linear programming method is used instead, to construct provably good suboptimal patrol policies. The state space is partitioned and the optimal cost-to-go or value function is restricted to be a constant over each partition. The resulting restricted system of linear inequalities embeds a family of Markov chains of lower dimension, one of which can be used to construct a lower bound on the optimal value function. In general, the construction of a lower bound requires the solution to a combinatorial problem. But the perimeter patrol problem exhibits a special structure that enables tractable linear programming formulation for the lower bound. This is demonstrated and...
5 citations