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Article

Computationally-Efficient Distributed Algorithms of Navigation of Teams of Autonomous UAVs for 3D Coverage and Flocking

School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney 2052, Australia
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Author to whom correspondence should be addressed.
Academic Editor: Abdessattar Abdelkefi
Drones 2021, 5(4), 124; https://doi.org/10.3390/drones5040124
Received: 22 September 2021 / Revised: 17 October 2021 / Accepted: 21 October 2021 / Published: 25 October 2021
(This article belongs to the Special Issue Conceptual Design, Modeling, and Control Strategies of Drones)
This paper proposes novel distributed control methods to address coverage and flocking problems in three-dimensional (3D) environments using multiple unmanned aerial vehicles (UAVs). Two classes of coverage problems are considered in this work, namely barrier and sweep problems. Additionally, the approach is also applied to general 3D flocking problems for advanced swarm behavior. The proposed control strategies adopt a region-based control approach based on Voronoi partitions to ensure collision-free self-deployment and coordinated movement of all vehicles within a 3D region. It provides robustness for the multi-vehicle system against vehicles’ failure. It is also computationally-efficient to ensure scalability, and it handles obstacle avoidance on a higher level to avoid conflicts in control with the inter-vehicle collision avoidance objective. The problem formulation is rather general considering mobile robots navigating in 3D spaces, which makes the proposed approach applicable to different UAV types and autonomous underwater vehicles (AUVs). However, implementation details have also been shown considering quadrotor-type UAVs for an example application in precision agriculture. Validation of the proposed methods have been performed using several simulations considering different simulation platforms such as MATLAB and Gazebo. Software-in-the-loop simulations were carried out to asses the real-time computational performance of the methods showing the actual implementation with quadrotors using C++ and the Robot Operating System (ROS) framework. Good results were obtained validating the performance of the suggested methods for coverage and flocking scenarios in 3D using systems with different sizes up to 100 vehicles. Some scenarios considering obstacle avoidance and robustness against vehicles’ failure were also used. View Full-Text
Keywords: cooperative control; coverage control; flocking control; Multi-Agent Systems; Navigation of Aerial Drones; UAVs; UAV Control Systems; UAV Swarm cooperative control; coverage control; flocking control; Multi-Agent Systems; Navigation of Aerial Drones; UAVs; UAV Control Systems; UAV Swarm
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MDPI and ACS Style

Elmokadem, T.; Savkin, A.V. Computationally-Efficient Distributed Algorithms of Navigation of Teams of Autonomous UAVs for 3D Coverage and Flocking. Drones 2021, 5, 124. https://doi.org/10.3390/drones5040124

AMA Style

Elmokadem T, Savkin AV. Computationally-Efficient Distributed Algorithms of Navigation of Teams of Autonomous UAVs for 3D Coverage and Flocking. Drones. 2021; 5(4):124. https://doi.org/10.3390/drones5040124

Chicago/Turabian Style

Elmokadem, Taha, and Andrey V. Savkin. 2021. "Computationally-Efficient Distributed Algorithms of Navigation of Teams of Autonomous UAVs for 3D Coverage and Flocking" Drones 5, no. 4: 124. https://doi.org/10.3390/drones5040124

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