Abstract
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.
Highlights
IntroductionCoverage control deals with problems where a certain region of interest needs to be surveyed whether using a single vehicle or multiple (i.e., using mobile wireless sensor networks (MWSNs))
There has been an increasing interest in mobile wireless sensor networks (MWSNs), where a number of networked autonomous vehicles can be deployed in different environments to achieve sensing tasks
Multi-Unmanned aerial vehicles (UAVs) systems have been emerging in various applications such as precision agriculture [9,10,11,12,13], aerial manipulation and transportation [14,15,16,17,18], search and rescue [14,19,20], firefighting [21], surveillance and monitoring [22,23], mapping and exploration [24,25,26], etc
Summary
Coverage control deals with problems where a certain region of interest needs to be surveyed whether using a single vehicle or multiple (i.e., using MWSNs). Tackling these problems with multi-vehicle systems has given rise to new challenges to traditional cooperative control in the field of coverage control [1,2,3,4,5,6,7,8]. Multi-UAV systems have been emerging in various applications such as precision agriculture [9,10,11,12,13], aerial manipulation and transportation [14,15,16,17,18], search and rescue [14,19,20], firefighting [21], surveillance and monitoring [22,23], mapping and exploration [24,25,26], etc
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