Observer-Based coverage control of unicycle mobile robot network in dynamic environment

Sun, Qihai; Chi, Ming; Liu, Zhiwei; He, Dingxin

doi:10.1016/j.jfranklin.2022.06.050

Cited by 7 publications

(7 citation statements)

References 20 publications

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“…As a branch of cooperative control of multi-agent systems [1][2][3][4], coverage control of multi-agent systems has gained more and more attention [5][6][7][8][9]. A decentralized control law [10] is proposed to drive a network of mobile robots to an optimal sensing configuration by using an adaptive control architecture.…”

Section: Introductionmentioning

confidence: 99%

“…Much attention has been focused on the coverage control of the unidentified region. With unknown environment information, a robust coverage control algorithm [6] is proposed to guide the unicycle robot network to the ideal configuration on the basis of an approximated density function. For a sensor network, the main object of coverage control is to drive the sensors to distribute over a region while aggregating in locations of their high interest [12].…”

Section: Introductionmentioning

confidence: 99%

“…For a sensor network, the main object of coverage control is to drive the sensors to distribute over a region while aggregating in locations of their high interest [12]. As we know, there is a considerable amount of literature on the coverage control of a region with multiple robots, such as [6][7][8][9]. A dynamic coverage planning technique is given in [7] which can eliminate the convexity requirement restrictions of the targeted area by using the K-means approach.…”

Section: Introductionmentioning

confidence: 99%

“…As was stated, for the coverage control of a sensor network, the optimal location of each sensor is affected by its interest element. Generally speaking, the interest elements are unknown, so that the observer-based coverage control turns out [6]. In [6], a state estimation algorithm [15] is firstly equipped on each sensor to estimate the information of the targeted region; then, the coverage control algorithm is given to guide the motion of each sensor to reach the optimal coverage configuration.…”

Section: Introductionmentioning

confidence: 99%

“…Generally speaking, the interest elements are unknown, so that the observer-based coverage control turns out [6]. In [6], a state estimation algorithm [15] is firstly equipped on each sensor to estimate the information of the targeted region; then, the coverage control algorithm is given to guide the motion of each sensor to reach the optimal coverage configuration. However, on one hand, it is important to consider that covering control is often associated with targeted regions that are typically expansive.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

RBFNN-Based Distributed Coverage Control on an Unknown Region

Zhang,

Wang

2023

Mathematics

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In this paper, we investigate the problem of achieving distributed coverage control of a mobile sensor network on an unknown region using local measurements. To accomplish this objective, each sensor is equipped with two-layer dynamics. The upper layer dynamic employs a completely distributed observer algorithm on the target region for state estimation of the density function. The lower layer dynamic utilizes a radial basis function neural network-based motion algorithm, which involves only the estimated state obtained by the upper layer dynamics, to guide the sensors towards an optimal coverage configuration. We demonstrate that with only the joint detectability of the partial outputs measurement, it is possible to achieve distributed coverage control in the unknown region without requiring additional information about the density function, communication topology associated with the sensors, or coupling gains. Finally, two examples are used to validate the theoretical findings.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

RBFNN-Based Distributed Coverage Control on an Unknown Region

Zhang,

Wang

2023

Mathematics

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Consensus of multi‐agent system with reaction‐diffusion terms and time delays via output‐feedback adaptive boundary control

Wan,

Yan,

et al. 2024

Adaptive Control & Signal

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SummaryMulti‐agent systems (MASs) are widely used in many necessary fields such as cybersecurity, precision agriculture, satellites, and smart grids. In many practical processes, a proportion of states cannot be obtained directly. Therefore, it is desired to design an observer. This article explores the utilization of output‐feedback adaptive control techniques to achieve consensus in MASs based on partial differential equations (PDEs) with reaction‐diffusion terms and time delays. First, in dealing with time‐invariant delays, an observer according to the Luenberger method is proposed to assess the state of agents. Convergence conditions of the estimated states are obtained by employing Lyapunov functions and Wirtinger inequality. Using the obtained estimated states, a boundary adaptive control strategy is proposed to make the error system consensus. The merit of this control method lies in the fact that communication between agents only occurs at the spatial boundary position, not throughout the entire spatial domain, and the parameters of the system can be constantly changed. Consensus criteria of MASs with time‐invariant delays are obtained by using the output‐feedback adaptive control, and the results are further generalized to the model with time‐varying delays. Lastly, two experimental scenarios are provided to show the practicality of the proposed theories.

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Designing a completely distributed observer with robustness against disturbances

Wang,

Zhang,

et al. 2024

Intl J Robust & Nonlinear

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Distributed observer is an effective scheme for state estimation of a targeted system, utilizing a network of sensors to perform local output measurements. In this article, the problem of designing a distributed observer for a linear time‐invariant system with external disturbances is addressed. The objective is to perform state estimation of such a system while simultaneously mitigating the impact of external disturbances and maintaining the distributed communication characteristics among the sensors. To achieve this, a completely distributed observer with robustness against disturbances is developed by combining the high‐gain observer technique and the adaptive coupling strength strategy. Initially, a traditional high‐gain observer is used for the state estimation on the observable subsystem, and subsequently a high‐gain observer without peaking is introduced to avoid the peaking phenomenon. Finally, numerical simulations are presented to verify the theoretical results.

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Observer-Based coverage control of unicycle mobile robot network in dynamic environment

Cited by 7 publications

References 20 publications

RBFNN-Based Distributed Coverage Control on an Unknown Region

RBFNN-Based Distributed Coverage Control on an Unknown Region

Consensus of multi‐agent system with reaction‐diffusion terms and time delays via output‐feedback adaptive boundary control

Designing a completely distributed observer with robustness against disturbances

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