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Improved Distributed Coverage Control for Robotic Visual Sensor Network under Limited Energy Storage

Azwirman Gusrialdi, Risvan Dirza, Takeshi Hatanaka, Masayuki Fujita


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.


Wireless capsule endoscopy, Image denoising, PSNR, SSIM, FSIM.

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