VBCA: A Virtual Forces Clustering Algorithm for Autonomous Aerial Drone Systems

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

Development and Validation of a LQR-Based Quadcopter Control Dynamics Simulation Model

5The growing applications involving unmanned aerial vehicles (UAVs) are requiring more advanced control algorithms to improve rotary-wing UAVs’ performance. To preliminarily tune such advanced controllers, an experimental approach could take a long time and also be dangerous for the vehicle and the onboard hardware components. In this paper, a simulation model of a quadcopter is developed and validated by the comparison of simulation results and experimental data collected during flight tests. For this purpose, an open-source flight controller for quadcopter UAVs is developed and a linear quadratic regulator (LQR) controller is implemented as the control strategy. The input physical quantities are experimentally measured; hence, the LQR controller parameters are tuned on the simulation model. The same tuning is proposed on the developed flight controller with satisfactory results. Finally, flight data and simulation results are compared showing a reliable approximation of the experimental data by the model. Because numerous state-of-the-art simulation models are available, but accurately validated ones are not easy to find, the main purpose of this work is to provide a reliable tool to evaluate the performance for this UAV configuration. DOI: 10.1061/(ASCE)AS.1943-5525.0001336. © 2021 American Society of Civil Engineers.partially_openopenAlessandro Minervini; Simone Godio; Giorgio Guglieri; Fabio Dovis; Alfredo BiciMinervini, Alessandro; Godio, Simone; Guglieri, Giorgio; Dovis, Fabio; Bici, Alfred

Multiple UAV systems: a survey

Nowadays, Unmanned Aerial Vehicles (UAVs) are used in many different applications. Using systems of multiple UAVs is the next obvious step in the process of applying this technology for variety of tasks. There are few research works that cover the applications of these systems and they are all highly specialized. The goal of this survey is to fill this gap by providing a generic review on different applications of multiple UAV systems that have been developed in recent years. We also present a nomenclature and architecture taxonomy for these systems. In the end, a discussion on current trends and challenges is provided.This work was funded by the Ministry of Economy, Industryand Competitiveness of Spain under Grant Nos. TRA2016-77012-R and BES-2017-079798Peer ReviewedPostprint (published version

Resilience Model for Teams of Autonomous Unmanned Aerial Vehicles (UAV) Executing Surveillance Missions

Teams of low-cost Unmanned Aerial Vehicles (UAVs) have gained acceptance as an alternative for cooperatively searching and surveilling terrains. These UAVs are assembled with low-reliability components, so unit failures are possible. Losing UAVs to failures decreases the team\u27s coverage efficiency and impacts communication, given that UAVs are also communication nodes. Such is the case of a Flying Ad Hoc Network (FANET), where the failure of a communication node may isolate segments of the network covering several nodes. The main goal of this study is to develop a resilience model that would allow us to analyze the effects of individual UAV failures on the team\u27s performance to improve the team\u27s resilience. The proposed solution models and simulates the UAV team using Agent-Based Modeling and Simulation. UAVs are modeled as autonomous agents, and the searched terrain as a two-dimensional M x N grid. Communication between agents permits having the exact data on the transit and occupation of all cells in real time. Such communication allows the UAV agents to estimate the best alternatives to move within the grid and know the exact number of all agents\u27 visits to the cells. Each UAV is simulated as a hobbyist, fixed-wing airplane equipped with a generic set of actuators and a generic controller. Individual UAV failures are simulated following reliability Fault Trees. Each affected UAV is disabled and eliminated from the pool of active units. After each unit failure, the system generates a new topology. It produces a set of minimum-distance trees for each node (UAV) in the grid. The new trees will thus depict the rearrangement links as required after a node failure or if changes occur in the topology due to node movement. The model should generate parameters such as the number and location of compromised nodes, performance before and after the failure, and the estimated time of restitution needed to model the team\u27s resilience. The study addresses three research goals: identifying appropriate tools for modeling UAV scenarios, developing a model for assessing UAVs team resilience that overcomes previous studies\u27 limitations, and testing the model through multiple simulations. The study fills a gap in the literature as previous studies focus on system communication disruptions (i.e., node failures) without considering UAV unit reliability. This consideration becomes critical as using small, low-cost units prone to failure becomes widespread

Design in Engineering: An Evaluation of Civilian and Military Unmanned Aerial Vehicle Platforms, Considering Smart Sensing with Ethical Design to Embody Mitigation Against Asymmetric Hostile Actor Exploitation

This report is written in part-fulfilment of personal output criteria for the Visiting Research Fellowship (Sir Richard Grenville Fellowship) at the Changing Character of War Centre, Pembroke College, Oxford, and the Centre for Sea Power and Strategy, Britannia Royal Naval College, Plymouth University at BRNC, Dartmouth. In this report I undertook an extensive analysis of the maritime UAV platform systems sector of a wide range of upstream manufacturing industry and downstream end user stakeholders. I consulted a global range of military and civilian users, to inform discussions around civilian UAV platforms which could be modified by hostile non-state actors, with emphasis on the littoral maritime region. This has strategic relevance to the United Kingdom, being an island-state with over 10,000 miles of coastline, c. 600 ports, and nearly 300 off-shore oil and gas platforms. In addition the UK has 14 dependencies together with a combined EEZ of 2.5 million square miles, the fifth largest in the world

Methods for the Efficient Deployment and Coordination of Swarm Robotic Systems

Swarming has been observed in many animal species, including fish, birds, insects and mammals. These biological observations have inspired mathematical models of distributed coordination that have been applied to the development of multi-agent robotic systems, such as collections of unmanned autonomous vehicles (UAVs). The advantages of a swarming approach to distributed coordination are clear: each agent acts according to a simple set of rules that can be implemented on resource-constrained devices, and so it becomes feasible to replicate agents in order to build more resilient systems. However, there remain significant challenges in making the approach practicable. This thesis addresses two of the most significant: coordination and scalability. New coordination algorithms are proposed here, all of which manage the problem of scalability by requiring only local proximity sensing between agents, without the need for any other communications infrastructure. A major source of inefficiency in the deployment of a swarm is ‘oscillation’: small movements of agents that arise as a side effect of the application of their rules but which are not strictly necessary in order to satisfy the overall system function. The thesis introduces a new metric for ‘oscillation’ that allows it to be identified and measured in swarm control algorithms. A new perimeter detection mechanism is introduced and applied to the coordination of goal-based swarms. The mechanism is used to improve the internal coordination of agents whilst maintaining a directional focus to the swarm; this is then analysed using the new metric. A mechanism is proposed to allow a swarm to exhibit a ‘healing’ behaviour by identifying internal perimeter edges (doughnuts) and then altering the movement of agents, based upon a simple criterion, to remove the holes; this also has the emergent effect of smoothing the outer edges of a swarm and creating a more uniform swarm structure. Area coverage is an important requirement in many swarm applications. Two new, efficient area-filling techniques are introduced here and exit conditions are identified to determine when a swarm has filled an area. In summary, the thesis makes significant contributions to the analysis and design of efficient control algorithms for the coordination of large scale swarms