A robotic sensor network is advantageous in performing a coverage task compared to the
static sensor network due to 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, i.e.
participate in the coverage task. This results in a degradation of coverage performance by
the robotic network. Furthermore, since in reality the mobile sensors have only a limited
energy storage, the movement of the sensors have to be as efficient as possible. This article
proposes a novel distributed algorithm in order to improve the coverage performance by
the robotic visual sensor network by guaranteeing the participation of all sensors in the coverage
task and considering the energy consumption of the sensors in the motion planning.
The algorithm is a combination of the standard gradient-based coverage algorithm and a
leader-following algorithm and is designed to maximize the joint detection probabilities of
the events in the region of interest. In addition, the standard coverage control law is further
modified in order to take into account the energy consumption of the sensors. The results
are validated through numerical simulations.
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