Coverage control for mobile anisotropic sensor networks

Abstract

Distributed algorithms for (re)configuring mobile sensors to cover a given area are important for autonomous multi-robot operations in application areas such as surveillance and environmental monitoring. Depending on the assumptions about the choice of the environment, the sensor models, the coverage metric, and the motion models of sensor nodes, there are different versions of the problem that have been formulated and studied. In this paper, we consider a system of holonomic mobile robots equipped with anisotropic sensors (e.g., limited field of view cameras) that are required to cover a polygonal region with polygonal obstacles to detect interesting events. We assume a given probability distribution of the events over a region. Motivated by scenarios where the sensing performance not only depends on the resolution of sensing but also on the relative orientation between the sensing axis and the event, we assume that the probability of detection of an event depends on both sensing parameters and the orientation of observation. We present a distributed gradient-ascent algorithm for reconfiguring the system of mobile robots so that the joint probability of detection of events over the whole region is maximized (i.e., positioning the mobile robots and determining their sensor parameters). As an example case study, we use a system of mobile robots equipped with limited field of view cameras with pan and zoom capabilities. We present simulation results demonstrating the performance of our algorithm.