Exploiting the use of information to improve coverage performance of robotic sensor networks

Abstract

A robotic sensor network is advantageous in performing a coverage task compared to the static sensor network because of its ability to self-deploy and self-reconfigure. However, since the sensor has a limited sensing range, when mobile sensors are initially deployed, sensors located far away from the region of interest may not be able to self-deploy themselves, that is, participate in the coverage task. This results in a degradation of coverage performance by the robotic network. This paper proposes a novel algorithm in order to improve the coverage performance by the whole mobile sensor network by guaranteeing the participation of all sensors in the coverage task. The algorithm is a combination of the standard gradient-based coverage algorithm and a leader-following algorithm and is designed to maximise the joint detection probabilities of the events in the region of interest. As a strategy, first a set of leader sensors are selected based on the information which each sensor has gathered. The rest of the sensors will follow their leaders until they have sufficient information on the region of interest and then switch to the standard coverage algorithm. The proposed algorithm can be performed in a distributed manner. The results are validated through several numerical simulations.