Distributed Cooperative Search with Collision Avoidance for a Team of Unmanned Aerial Vehicles Using Gradient Optimization
Publication: Journal of Aerospace Engineering
Volume 30, Issue 1
Abstract
This paper addresses the cooperative search problem for a team of unmanned aerial vehicles (UAVs) with limited field-of-view (FOV) and available overload constraints. First, the models of environment, UAV, image sensor, and communication are established. Second, a modified distributed information fusion strategy based on the Bayesian rule is proposed, which can make all the individual probability maps converge to the same one and reflect the true existence or nonexistence of targets within each cell. Third, a distributed gradient-based optimization method for path planning involved in the cooperative search is proposed and the available overload constraint of the UAV can be taken into account. Fourth, the aforementioned distributed gradient-based optimization method is improved by involving collision avoidance, establishing reasonable safety distance constraints, and using the Lagrange multiplier. Finally, the correctness and effectiveness of the proposed method are validated and demonstrated via simulations.
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Acknowledgments
This work was supported by the Armament Fund.
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Published In
Journal of Aerospace Engineering
Volume 30 • Issue 1 • January 2017
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Nov 30, 2015
Accepted: May 4, 2016
Published online: Jul 15, 2016
Discussion open until: Dec 15, 2016
Published in print: Jan 1, 2017
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