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Cooperative control of UAV swarm via information measures

Cooperative control of UAV swarm via information measures Purpose This study aims to investigate the rulebased decentralised control framework for a swarm of UAVs carrying out a cooperative ground target engagement mission scenario.Designmethodologyapproach This study is to investigate the rulebased decentralised control framework for missions which require highlevel cooperation between team members. The design of the authors control strategy is based on agentlevel interactions. Different to a centralized task assignment algorithm, the cooperation of the agents is entirely implicit. The behaviour of the UAVs is governed by rule sets which ultimately lead to cooperation at a system level. The information theoretic measures are adopted to estimate the value of possible future actions. The prediction model is further considered to enhance the team performance in the scenario where there are tight coupled task constraints.Findings The simulation study evaluates the performance of the decentralised controller and compares it with a centralised controller quantitatively. The results show that the proposed approach leads to a highly cooperative performance of the group without the need for a centralised control authority. The performance of the decentralised control depends on the complexity of the coupled task constraints. It can be improved by using a prediction model to provide information such as the intentions of the neighbours that is not available locally.Originalityvalue The achievable performance of the decentralised control was considered to be low due to the absence of communication and little global coordinating information. This study demonstrated that the decentralised control can achieve highly cooperative performance. The achievable performance is related to the complexity of the coupled constraints and the accuracy of the prediction model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Intelligent Unmanned Systems Emerald Publishing

Cooperative control of UAV swarm via information measures

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References (30)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
2049-6427
DOI
10.1108/IJIUS-01-2013-0001
Publisher site
See Article on Publisher Site

Abstract

Purpose This study aims to investigate the rulebased decentralised control framework for a swarm of UAVs carrying out a cooperative ground target engagement mission scenario.Designmethodologyapproach This study is to investigate the rulebased decentralised control framework for missions which require highlevel cooperation between team members. The design of the authors control strategy is based on agentlevel interactions. Different to a centralized task assignment algorithm, the cooperation of the agents is entirely implicit. The behaviour of the UAVs is governed by rule sets which ultimately lead to cooperation at a system level. The information theoretic measures are adopted to estimate the value of possible future actions. The prediction model is further considered to enhance the team performance in the scenario where there are tight coupled task constraints.Findings The simulation study evaluates the performance of the decentralised controller and compares it with a centralised controller quantitatively. The results show that the proposed approach leads to a highly cooperative performance of the group without the need for a centralised control authority. The performance of the decentralised control depends on the complexity of the coupled task constraints. It can be improved by using a prediction model to provide information such as the intentions of the neighbours that is not available locally.Originalityvalue The achievable performance of the decentralised control was considered to be low due to the absence of communication and little global coordinating information. This study demonstrated that the decentralised control can achieve highly cooperative performance. The achievable performance is related to the complexity of the coupled constraints and the accuracy of the prediction model.

Journal

International Journal of Intelligent Unmanned Systems – Emerald Publishing

Published: Jul 26, 2013

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