Multiple agent coordination for stochastic target interception using MILP

In this paper we present an approach to solving a stochastic multi-target interception problem. In the multi-target interception problem, a team of mobile sensors is tasked with intercepting a set of potential targets to reduce appropriately assigned damage cost. Our principal contribution is to express a stochastic version of the problem with a generalized cost as a mixed-integer linear program so that optimal sensor motion can be computed efficiently. Indeed, our optimization program for the stochastic problem has similar computational costs as the optimization program for the corresponding deterministic problem. Our solution presumes that the system can be approximated by linear dynamics and Gaussian noise, with Gaussian localization uncertainty.