Suboptimal decentralized blanket coverage control of mobile autonomous sensor networks

Abstract

We propose a novel distributed control algorithm for self-deployment of a network of autonomous mobile sensors in the problem of blanket coverage. The objective is to deploy sensors in a given and a priori unknown bounded region of arbitrary shape so that any its point is sensed by at least one sensor. Moreover, this objective should be achieved by as few sensors as possible. The proposed algorithm is decentralized, computationally inexpensive, employs information exchange only between currently nearest neighbors in the sensor network, and ensures an eventual stopover of the entire network. A mathematically rigorous proof of finite time convergence of the proposed algorithm is provided. Its performance is illustrated by computer simulations carried out for various scenarios.

Distributed Navigation of Multi-Robot Systems For Sensing Coverage

“…However, a random deployment might leave a coverage hole or mobile robotic sensors might be denser in some parts of the area and leaving the other parts without any coverage. We present some of the algorithms [4,113] having a characteristic of randomized movement of mobile robotic sensors for the full coverage.…”

“…Figure 2.6: Blanket coverage over a region -a randomized approach [4] Similar to [4], another blanket coverage algorithm has been presented in [113].…”

“…This algorithm [113] differs from [4] in two ways: Firstly the above mentioned Stage-A and Stage-B is executed in parallel and secondly it gives a rigorous mathematical proof that the full blanket convergence will be achieved within finite time. However, this algorithm considers a slightly excessive number of mobile robotic sensors and it solution is considered to be sub-optimal.…”

Finite time coverage tracking algorithm of maneuvering target by multiple mobile agents

“…The problem requires a group of individuals with perceptual, communication, computing, and mobile capabilities to perform specific tasks in a certain area, such as rescue (Miah et al, 2015), hunt (Leonard and Olshevsky, 2013), environmental monitoring (Zuo et al, 2014), deep sea detection (Wang and Hussein, 2007), and so on. Coverage problems can be classified as region coverage (Gusrialdi et al, 2009; Liu et al, 2006; Savkin et al, 2015), boundary coverage (Gupta et al, 2015; Luo, 2012; Nasimov and Matveev, 2015) and target coverage (Bikramaditya et al, 2016; Sun, 2015).…”