Co-Regulated Information Consensus with Delays for Multi-Agent UAS

Fernando, Chandima; Detweiler, Carrick; Bradley, Justin

doi:10.1109/cdc42340.2020.9304068

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…Increasing the performance of a decentralized multi-agent system has been intensively studied in the last decade, where significant progress has been made in the field of distributed control algorithms including algorithms for swarming [ 7 , 8 , 9 ], consensus [ 10 , 11 , 12 ], and rendezvous [ 13 ]. The ability of multi-agent systems to execute a certain task in parallel has been widely exploited in many applications, including logistics in autonomous warehouses [ 14 ], the exploration of unknown environments [ 15 ], manipulation [ 16 , 17 ], surveillance [ 18 , 19 ], search-and-rescue [ 20 ], interaction with animal species [ 21 , 22 ], and sensor networks [ 23 , 24 , 25 ].…”

Section: Literature Overviewmentioning

confidence: 99%

Algebraic Connectivity Control in Distributed Networks by Using Multiple Communication Channels

Griparic

2021

Sensors

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The effectiveness of collaboration in distributed networks, such as sensor networks and multi-agent systems, relies on nodes’ ability to exchange information. The availability of various communication protocols with different technical properties opens the possibility to guarantee connectivity during a system’s operation in any condition. A communication network can be represented by a graph on which connectivity can be expressed by a well-known algebraic connectivity value or Fiedler value. It is one of the most important tools used in many applications where connectivity preservation is required. In this paper, a trust-based consensus algorithm for algebraic connectivity estimation has been implemented. To guarantee the accomplishment of the global objective and the system’s performance, our contributions include: (i) a novel decentralized framework for combining multiple communication channels in a resulting channel and (ii) a decentralized algebraic connectivity control law that dynamically changes the number of agents in the system during operation. The proposed algebraic connectivity control strategy has been evaluated in simulations and in a real multi-robot system using two channels with different properties and initial topologies.

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