Resolution-Directed Optimization-based Distributed Sensing
In this paper we study the problem of optimal zone coverage, using distributed sensing, i.e. a group of collaborating sensors. We formulate the problem as an optimization problem with time-varying cost function. We examine the case where a group of elevated imaging sensors look down to and form the map of a 2-dimensional environment at a pre-specified resolution. The sensors solve an optimization problem that attempts to optimize a time-varying cost function. The cost at any time instance measures the distance between the desired resolution function and the achieved resolution until the previous time instant. We discuss the numerical implementation challenges of this approach and demonstrate its performance on a numerical example.