We consider the positioning problem of aerial drone systems for efficient three-dimensional (3-D) coverage. Our solution draws from molecular geometry, where forces among electron pairs surrounding a central atom arrange their positions. In this paper, we propose a 3-D clustering algorithm for autonomous positioning (VBCA) of aerial drone networks based on virtual forces. These virtual forces induce interactions among drones and structure the system topology. The advantages of our approach are that (1) virtual forces enable drones to self-organize the positioning process and (2) VBCA can be implemented entirely localized. Extensive simulations show that our virtual forces clustering approach produces scalable 3-D topologies exhibiting near-optimal volume coverage. VBCA triggers efficient topology rearrangement for an altering number of nodes, while providing network connectivity to the central drone. We also draw a comparison of volume coverage achieved by VBCA against existing approaches and find VBCA up to 40 more efficient.
Brust and Strimbu @cite_14 introduce a UAV networked swarm model for forestry assessment and environmental monitoring. The UAV swarm is able to establish, maintain multi-hop connectivity and avoid obstacles, while assessing the forest environment (e.g. tree localization, tree mapping). @cite_5 use Linear Model Predictive Control (LMPC) to implement line abreast, triangular and cross formation flights for drones in simulations and experiments. The Reconfigurable Flight Control System Architecture (RFCSA) @cite_9 is a control framework for small UAVs. RFCSA utilizes a different module for each function of a drone to minimize the complexity of implementation and coordination during the flight.
@cite_5 @cite_9 @cite_14
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A team of three Unmanned Aerial Vehicles (UAVs) accomplishes a line abreast, triangular and cross formation based on high-level Linear Model Predictive Control (LMPC). All flight tests respect Reynold's rules of flocking, where the UAVs avoid collisions with nearby flockmates, attempt to match velocity of other team members and attempt to stay close to other flockmates. A linear system identification model is at the base of the error dynamics describing the formation control algorithm. The main contribution of this paper lies in the use of LMPC to implement multiple formations on UAVs in simulation and using the Qball-X4 quadrotor. Small Unmanned Aerial Vehicles (UAVs) have been proposed for use in a variety of areas including hazard analysis, disaster monitoring, agricultural mapping, and so on. Currently, the development of flight control systems (FCS) for small UAVs is complicated, time-consuming and error-prone. To address these challenges, we present a reconfigurable flight control system architecture (RFCSA) for small UAVs. RFCSA allows rapidly integrating hardware modules and verifying control laws. It utilizes a modular-based framework, in which implementation details of a typical function are packaged into a function module. In addition, each function module in RFCSA is stand-alone with its own processors, memories, power conversion and communication interfaces. In this way, the system designer could be able to focus on the system implementation, rather than pay much attention to the design details of low-level functions. Moreover, an event-driven Service-Oriented Architectures (SOA) is proposed to minimize the coupling between modules and improve the performance of inter-module interactions. The paper is organized as follows: Firstly, the challenges and requirements for small UAVs' flight control systems are discussed. Secondly, the hardware architecture based on modular concept is developed. Thirdly, event driven SOA is proposed, and the mechanisms for modules to share information and coordinate activities are introduced. Finally, the conclusion and future work is pointed out. Autonomous Unmanned Aerial Vehicles (UAVs) have gained popularity due to their many potential application fields. Alongside sophisticated sensors, UAVs can be equipped with communication adaptors aimed for inter-UAV communication. Inter-communication of UAVs to form a UAV swarm raises questions on how to manage its communication structure and mobility. In this paper, we consider therefore the problem of establishing an efficient swarm movement model and a network topology between a collection of UAVs, which are specifically deployed for the scenario of high-quality forest-mapping.