Distributed Global Connectivity Maintenance and Control of Multi-Robot Networks

Cai, Da; Wu, Sentang; Deng, Jia

doi:10.1109/access.2017.2708422

Cited by 14 publications

(7 citation statements)

References 20 publications

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“…Due to the high operating efficiency of the embedded system, the generation time for each new formation was within 15 s, which meets the requirements of small UAV formations. The formation transformation method of the UAVs in the experiment comes from study [35], and the communication control method between UAVs comes from study [36].…”

Section: Flight Verification and Resultsmentioning

confidence: 99%

Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things

Yao

Wen

2019

Sensors

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Multi-agent hybrid social cognitive optimization (MAHSCO) based on the Internet of Things (IoT) is suggested to solve the problem of the generation of formations of unmanned vehicles. Through the analysis of the unmanned vehicle formation problem, formation principles, formation scale, unmanned vehicle formation safety distance, and formation evaluation indicators are taken into consideration. The application of the IoT enables the optimization of distributed computing. To ensure the reliability of the formation algorithm, the convergence of MAHSCO has been proved. Finally, computer simulation and actual unmanned aerial vehicle (UAV) formation generation flight generating four typical formations are carried out. The result of the actual UAV formation generation flight is consistent with the simulation experiment, and the algorithm performs well. The MAHSCO algorithm based on the IoT is proved to be able to generate formations that meet the mission requirements quickly and accurately.

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Section: Flight Verification and Resultsmentioning

confidence: 99%

Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things

Yao

Wen

2019

Sensors

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“…The communication network of the centralised dispatch system has a star topology centred on the dispatch centre, and each communication link is bidirectional. The distributed system only requires communication network topology connectivity [8], even joint connection [9]. The communication link can be bidirectional or unidirectional [10].…”

Section: Comparison Of Centralised and Distributed Ed Methodsmentioning

confidence: 99%

Distributed economic dispatch method for power system based on consensus

Jian

Zhou

Zhao

et al. 2020

IET Renewable Power Generation

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This study performs an extensive review on distributed economic dispatch method for the power system based on consensus. It covers the comparison of centralised and distributed economic dispatch method in terms of system structure, performance requirement and solution process. The key links in the process of solving economic dispatch problem are summarised, and the advantages and disadvantages of the existing distributed economic dispatch algorithm are reviewed. Furthermore, the possible research directions, from the authors' point of view, are also provided in this study.

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“…where ij pp − is the adjacency distance between robot i and j,  is a tuning parameter. In this paper, we define The weighted Laplacian matrix of the graph G is defined as [19] L  is defined as the algebraic connectivity to measure the connectivity of a graph ，and the larger the 2  is, the stronger the graph connectivity is.…”

Section: Preliminaries a Graph Theory And Global Connectivitymentioning

confidence: 99%

“…In addition, strong connectivity will take up more unnecessary network resources, which is not conducive to the execution of overall tasks. To solve this problem, a distributed control algorithm is proposed in [19] to maintain, enhance, and reduce the global connectivity online, according to different stages of tasks.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Robust Connectivity Control in Flocking of Multi-Robot Systems

Gong

et al. 2020

IEEE Access

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In this paper, a global connectivity control method for decentralized multi-robot systems is proposed. This method can achieve decentralized connectivity control of multi-robot network under disturbances, which has no effect on the objective flocking control. Based on the gradient between the connectivity and robot positions, the proposed connectivity control method can make each robot move along the desired gradient direction, so as to achieve the control of the global connectivity. Indeed, the flocking method based on the potential of attraction and repulsion can ensure that the distance between robots is stable within the desired range. Then the security of flocking and the stability of communication are guaranteed. It is proved in this paper that both connectivity and objective flocking control have no effect on the stability of each other, under the condition that both controllers are bounded. Therefore, the global connectivity and configuration of the system can achieve the desired states. In addition, a robust control method based on integral sliding mode is designed in this paper, which can counteract the external disturbance and ensure the ideal dynamics of multi-robot systems. Finally, several numerical simulations are given to validate the effectiveness of the proposed control methods. INDEX TERMS Multi-robot systems, distributed estimation, global connectivity control, potential energy function, robust control.

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Distributed Global Connectivity Maintenance and Control of Multi-Robot Networks

Cited by 14 publications

References 20 publications

Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things

Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things

Distributed economic dispatch method for power system based on consensus

Decentralized Robust Connectivity Control in Flocking of Multi-Robot Systems

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