Long-term Informative Path Planning with Autonomous Soaring

The ability of UAVs to cover large areas efficiently is valuable for information gathering missions. For long-term information gathering, a UAV may extend its endurance by accessing energy sources present in the atmosphere. Thermals are a favourable source of wind energy and thermal soaring is adopted in this thesis to enable long-term information gathering. This thesis proposes energy-constrained path planning algorithms for a gliding UAV to maximise information gain given a mission time that greatly exceeds the UAV's endurance. This thesis is motivated by the problem of probabilistic target-search performed by an energy-constrained UAV, which is tasked to simultaneously search for a lost ground target and explore for thermals to regain energy. This problem is termed informative soaring (IFS) and combines informative path planning (IPP) with energy constraints. IFS is shown to be NP-hard by showing that it has a similar problem structure to the weight-constrained shortest path problem with replenishments. While an optimal solution may not exist in polynomial time, this thesis proposes path planning algorithms based on informed tree search to find high quality plans with low computational cost. This thesis addresses complex probabilistic belief maps and three primary contributions are presented: • First, IFS is formulated as a graph search problem by observing that any feasible long-term plan must alternate between 1) information gathering between thermals and 2) replenishing energy within thermals. This is a first step to reducing the large search state space. • The second contribution is observing that a complex belief map can be viewed as a collection of information clusters and using a divide and conquer approach, cluster tree search (CTS), to efficiently find high-quality plans in the large search state space. In CTS, near-greedy tree search is used to find locally optimal plans and two global planning versions are proposed to combine local plans into a full plan. Monte Carlo simulation studies show that CTS produces similar plans to variations of exhaustive search, but runs five to 20 times faster. The more computationally efficient version, CTSDP, uses dynamic programming (DP) to optimally combine local plans. CTSDP is executed in real time on board a UAV to demonstrate computational feasibility. • The third contribution is an extension of CTS to unknown drifting thermals. A thermal exploration map is created to detect new thermals that will eventually intercept clusters, and therefore be valuable to the mission. Time windows are computed for known thermals and an optimal cluster visit schedule is formed. A tree search algorithm called CTSDrift combines CTS and thermal exploration. Using 2400 Monte Carlo simulations, CTSDrift is evaluated against a Full Knowledge method that has full knowledge of the thermal field and a Greedy method. On average, CTSDrift outperforms Greedy in one-third of trials, and achieves similar performance to Full Knowledge when environmental conditions are favourable

Coordination on Systems of Multiple UAVs

Esta tesis trata acerca de métodos para coordinar las trayectorias de un sistema de Vehículos Aéreos no Tripulados y Autónomos (en adelante UAVs). El primer conjunto de técnicas desarrolladas durante la tesis se agrupan dentro de las técnicas de planificación de trayectorias. En este caso, el objetivo es generar planes de vuelo para un conjunto de vehículos coordinadamente de forma que no se produzcan colisiones entre ellos. Además, este tipo de técnicas puede usarse para modificar el plan de vuelo de un subconjunto de UAVs en tiempo real. Entre los algoritmos desarrollados en la tesis podemos destacar la adaptación de algoritmos evolutivos como los Algoritmos Genéticos y el Particle Swarm (Enjambre de Partículas), la incorporación de nuevas formas de muestreo del espacio para la aplicación del algoritmo Optimal Rapidly Exploring Random Trees (RRT*) en sistemas multi-UAV usando técnicas de muestreo novedosas. También se ha estudiado el comportamiento de parte de estos algoritmos en situaciones variables de incertidumbre del estado del sistema. En particular, se propone el uso del Filtro de Partículas para estimar la posición relativa entre varios UAVs. Además, se estudia la aplicación de métodos reactivos para la resolución de colisiones en tiempo real. Esta tesis propone un nuevo algoritmo para la resolución de colisiones entre múltiples UAVs en presencia de obstáculos fijos llamado G-ORCA. Este algoritmo soluciona varios problemas que han surgido al aplicar el algoritmo ORCA en su variante 3D en sistemas compuestos por vehículos reales. Su seguridad se ha demostrado tanto analíticamente, como empíricamente en pruebas con sistemas reales. De hecho, durante esta tesis numerosos experimentos en sistemas multi-UAV reales compuestos hasta por 4 UAVs han sido ejecutados. En dichos experimentos, se realiza una coordinación autónoma de UAVs en las que se asegura la ejecución de trayectorias libres de colisiones garantizando por tanto la seguridad del sistema. Una característica reseñable de esta tesis es que los algoritmos desarrollados han sido probados e integrados en sistemas más complejos que son usados en aplicaciones reales. En primer lugar, se presenta un sistema para aumentar la duración del vuelo de planeadores aprovechando las corrientes ascendentes de viento generadas por el calor (térmicas). En segundo lugar, un sistema de detección y resolución de colisiones coordinado para sistemas con múltiples UAVs reactivo ha sido diseñado, desarrollado y probado experimentalmente. Este sistema ha sido integrado dentro de un sistema automático de construcción de estructuras mediante múltiples UAVs.The aim of this thesis is to propose methods to coordinately generate trajectories for a system of Autonomous Unmanned Aerial Vehicles (UAVs). The first set of proposed techniques developed in this thesis can be defined as trajectory planning techniques. In this case, the objective is to generate coordinated flight plans for a system of UAVs in such a way that no collision are produced among each pair of UAVs. Besides, these techniques can be applied online in order to modify the original flight plan whenever a potential collision is detected. Amongst the developed algorithms in this thesis we can highlight the adaptation of evolutionary algorithms such as Genetic Algorithms and Particle Swarm, and the application of Optimal Rapidly Exploring Random Trees (RRT*) algorithm into a system of several UAVs with novel sampling techniques. In addition, many of these techniques have been adapted in order to be applicable when only uncertain knowledge of the state of the system is available. In particular, the use of the Particle Filter is proposed in order to estimate the relative position between UAVs. The estimation of the position as well as the uncertainty related to this estimation are then taken into account in the conflict resolution system. All techniques proposed in this thesis have been validated by performing several simulated and real tests. For this purpose, a method for randomly generating a huge test batch is presented in chapter 3. This will allow to test the behavior of the proposed methods in a great variety of situations. During the thesis, several real experimentations with fleets composed by up to four UAVs are presented. In these experiments, the UAVs in the system are automatically coordinated in order to ensure collision-free trajectories and thus guarantee the safety of the system. The other main topic of this thesis is the application of reactive methods for real-time conflict resolution. This thesis proposes a novel algorithm for collision resolution amongst multiple UAVs in the presence of static obstacles, which has been called Generalized-Optimal Reciprocal Collision Avoidance (G-ORCA). This algorithm overcomes several issues that have been detected into the algorithm 3D-ORCA in real applications. A remarkable characteristic of this thesis is that the developed algorithms have been applied as a part of more complex systems. First, a coordinated system for flight endurance extension of gliding aircrafts by profiting the ascending wind is presented. Second, a reactive collision avoidance block has been designed, developed and tested experimentally based in the aforementioned G-ORCA algorithm. This block has been integrated into a system for assembly construction with multiple UAVs

Perpetual flight in flow fields

Tese de Doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201

The Unmanned Aerial Vehicle Routing and Trajectory Optimisation Problem, a Taxonomic Review

Over the past few years, Unmanned Aerial Vehicles (UAVs) have become more and more popular. The complexity of routing UAVs has not been fully investigated in the literature. In this paper, we provide a formal definition of the UAV Routing and Trajectory Optimisation Problem (UAVRTOP). Next, we introduce a taxonomy and review recent contributions in UAV trajectory optimisation, UAV routing and articles addressing these problems, and their variants, simultaneously. We conclude with the identification of future research opportunities.<br/

Modelling the dynamic flight behaviour of birds in different frames of reference

In this thesis I consider two aspects – energetics and guidance – of two dynamic flight behaviours performed by birds – dynamic soaring and prey pursuit. Uniting the thesis is the collection and modelling of bird trajectory data in different frames of reference to make inferences on dynamic flight behaviour. In particular, I collect data in a camera-fixed reference frame to model the dynamic soaring flight trajectories of Manx shearwater in an aerodynamic reference frame, whereas I model the attack trajectories of Harris’ hawks in both an inertial and a background frame of reference using data collected in an Earth-fixed frame of reference. The output of my investigation into the energetics of dynamic soaring is the first empirical demonstration of dynamic soaring outside the albatrosses, the formulation of a new metric for identifying and quantifying dynamic soaring, and the demonstration that the large-scale distribution of the Manx shearwater is affected by their dynamic soaring behaviour. The output of my investigation into the guidance of prey pursuit is the finding that Harris’ hawk attack trajectories are well modelled by the proportional navigation (PN) guidance law commonly used by homing missiles. However, I also show that a guidance law that can be mechanised using only visual information – rather than the inertial and visual information required by PN – also successfully fits attack trajectory data. Finally, I propose a method for analysing eye-in-head movements during dynamic flight in birds, and I find that Harris’ hawks limit eye-in-head movement during terminal pursuit, a necessary condition to implement PN guidance. In being reflective about the reference frames in which I model bird behaviour and, in cases, by modelling the same data in different reference frames, I expose the utility of the reference frame concept in analysing biological systems

Aerial collective systems

Deployment of multiple flying robots has attracted the interest of several research groups in the recent times both because such a feat represents many interesting scientific challenges and because aerial collective systems have a huge potential in terms of applications. By working together, multiple robots can perform a given task quicker or more efficiently than a single system. Furthermore, multiple robots can share computing, sensing and communication payloads thus leading to lighter robots that could be safer than a larger system, easier to transport and even disposable in some cases. Deploying a fleet of unmanned aerial vehicles instead of a single aircraft allows rapid coverage of a relatively larger area or volume. Collaborating airborne agents can help each other by relaying communication or by providing navigation means to their neighbours. Flying in formation provides an effective way of decongesting the airspace. Aerial swarms also have an enormous artistic potential because they allow creating physical 3D structures that can dynamically change their shape over time. However, the challenges to actually build and control aerial swarms are numerous. First of all, a flying platform is often more complicated to engineer than a terrestrial robot because of the inherent weight constraints and the absence of mechanical link with any inertial frame that could provide mechanical stability and state reference. In the first section of this chapter, we therefore review this challenges and provide pointers to state-of-the-art methods to solve them. Then as soon as flying robots need to interact with each other, all sorts of problems arise such as wireless communication from and to rapidly moving objects and relative positioning. The aim of section 3 is therefore to review possible approaches to technically enable coordination among flying systems. Finally, section 4 tackles the challenge of designing individual controllers that enable a coherent behavior at the level of the swarm. This challenge is made even more difficult with flying robots because of their 3D nature and their motion constraints that are often related to the specific architectures of the underlying physical platforms. In this third section is complementary to the rest of this book as it focusses only on methods that have been designed for aerial collective systems

Feature Papers of Drones - Volume I

[EN] The present book is divided into two volumes (Volume I: articles 1–23, and Volume II: articles 24–54) which compile the articles and communications submitted to the Topical Collection ”Feature Papers of Drones” during the years 2020 to 2022 describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles (drones). Articles 1–8 are devoted to the developments of drone design, where new concepts and modeling strategies as well as effective designs that improve drone stability and autonomy are introduced. Articles 9–16 focus on the communication aspects of drones as effective strategies for smooth deployment and efficient functioning are required. Therefore, several developments that aim to optimize performance and security are presented. In this regard, one of the most directly related topics is drone swarms, not only in terms of communication but also human-swarm interaction and their applications for science missions, surveillance, and disaster rescue operations. To conclude with the volume I related to drone improvements, articles 17–23 discusses the advancements associated with autonomous navigation, obstacle avoidance, and enhanced flight plannin

Systems, aerodeceleration, and structural design of a high-G, rapid response, deployable autonomous aerial surveillance vehicle

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1997.Includes bibliographical references (p. 123-127).The MIT/Draper Technology Development Partnership Project is a two year initiative between MIT's Department of Aeronautics and Astronautics and Draper Laboratory (the funding customer) to develop an innovative, first-of-a-kind system. Through in-depth market research. concept generation. and reviews with Draper. the Wide Area Surveillance Projectile (WASP) was chosen as the lead technology demonstration project. The WASP is a gun-launched projectile in the 5"/54 NAVY to 155 mm ARMY class of munitions that transforms into a powered flight vehicle after traveling a ballistic trajectory. Once transformed, the WASP performs visual imaging reconnaissance and relays field data to the user via a Satcom or UAV signal link. This thesis covers much of the work conducted in the first year of the program. and focuses on Ballistics and aerodeceleration. Structures, and Systems Interface Design of the WASP. Although the two year timeline for the program precludes building the complete system, a series of "long-poles" are being used to demonstrate the concept functionality and feasibility for possible prototype development. These long-poles include the development of high-g composite structures, deployable flight surfaces. and a two-stroke propulsion system. as well as a virtual ground station with sensors/communications subsystems. and finally a drop-test flyer that will perform the vehicles intended mission scenario.by Cory R.A. Hallam.M.Eng