Дисертації з теми "Uninhabited Aerial Vehicles"

Thesis (Degree of Aeronautical and Astronautical Engineer) Naval Postgraduate School, June 1998.
Thesis advisor(s): Garth V. Hobson, David W. Netzer. "June 1998." Includes bibliographical references (p. 73). Also available online.

Thesis (M.S. in Mechanical Engineering)--Naval Postgraduate School, June 2009.
Thesis Advisor(s): Lee, Deok Jin ; Kaminer, Issac I. "June 2009." Description based on title screen as viewed on 13 July 2009. Author(s) subject terms: Unmanned Aerial Vehicle, UAV, extremum seeking, simulink, high bandwidth communication links, SNR Model, coordinated control, cooperative control, decentralized control, wireless sensor network. Includes bibliographical references (p. 51). Also available in print.

Operation of Unmanned Air Vehicles (UAVs) has increased significantly over the past few years. However, routine operation in non-segregated airspace remains a challenge, primarily due to nature of the environment and restrictions and challenges that accompany this. Currently, tight human control is envisaged as a means to achieve the oft quoted requirements of transparency , equivalence and safety. However, the problems of high cost of human operation, potential communication losses and operator remoteness remain as obstacles. One means of overcoming these obstacles is to devolve authority, from the ground controller to an on-board system able to understand its situation and make appropriate decisions when authorised. Such an on-board system is known as an Autonomous System. The nature of the autonomous system, how it should be designed, when and how authority should be transferred and in what context can they be allowed to control the vehicle are the general motivation for this study. To do this, the system must overcome the negative aspects of differentiators that exist between UASs and manned aircraft and introduce methods to achieve required increases in the levels of versatility, cost, safety and performance. The general thesis of this work is that the role and responsibility of an airborne autonomous system are sufficiently different from those of other conventionally controlled manned and unmanned systems to require a different architectural approach. Such a different architecture will also have additional requirements placed upon it in order to demonstrate acceptable levels of Transparency, Equivalence and Safety. The architecture for the system is developed from an analysis of the basic requirements and adapted from a consideration of other, suitable candidates for effective control of the vehicle under devolved authority. The best practices for airborne systems in general are identified and amalgamated with established principles and approaches of robotics and intelligent agents. From this, a decision architecture, capable of interacting with external human agencies such as the UAS Commander and Air Traffic Controllers, is proposed in detail. This architecture has been implemented and a number of further lessons can be drawn from this. In order to understand in detail the system safety requirements, an analysis of manned and unmanned aircraft accidents is made. Particular interest is given to the type of control moding of current unmanned aircraft in order to make a comparison, and prediction, with accidents likely to be caused by autonomously controlled vehicles. The effect of pilot remoteness on the accident rate is studied and a new classification of this remoteness is identified as a major contributor to accidents A preliminary Bayesian model for unmanned aircraft accidents is developed and results and predictions are made as an output of this model. From the accident analysis and modelling, strategies to improve UAS safety are identified. Detailed implementations within these strategies are analysed and a proposal for more advanced Human-Machine Interaction made. In particular, detailed analysis is given on exemplar scenarios that a UAS may encounter. These are: Sense and Avoid , Mission Management Failure, Take Off/Landing, and Lost Link procedures and Communications Failure. These analyses identify the nature of autonomous, as opposed to automatic, operation and clearly show the benefits to safety of autonomous air vehicle operation, with an identifiable decision architecture, and its relationship with the human controller. From the strategies and detailed analysis of the exemplar scenarios, proposals are made for the improvement of unmanned vehicle safety The incorporation of these proposals into the suggested decision architecture are accompanied by analysis of the levels of benefit that may be expected. These suggest that a level approaching that of conventional manned aircraft is achievable using currently available technologies but with substantial architectural design methodologies than currently fielded.

Three-dimensional mapping and modeling can contribute to knowledge about the real world. Techniques are largely driven by available technology and typically involve expensive equipment and expert skill. Recent advances have led to low-cost remotely sensed data collection and generation of 3D terrain models using Uninhabited Aerial Vehicles (UAV) and Structure from Motion (SfM) processing software. This research presents a low-cost alternative to 3D mapping by pairing UAV collection methods with three SfM processing techniques. Surface models are generated from the same image set captured from a low-cost UAV coupled with a digital camera. Accuracy of resulting models identifies strengths and weaknesses of each technique. Analysis of different slope ranges investigates the divide at which surfaces generated become less reliable. This research provides a deeper understanding of the strengths and limitations of emerging technologies used together in a fresh approach to photogrammetry.

Thesis (M.S. in Aeronautical Engineering)--Naval Postgraduate School, June 1990.
Thesis Advisor(s): Howard, Richard M. Second Reader: Lindsey, Gerald H. "June 1990." Description based on signature page as viewed on October 21, 2009. DTIC Identifier(s): Composite materials, ducted fan, airframes, vertical takeoff aircraft, remotely piloted vehicles. Author(s) subject terms: UAV, composites, AROD, TDF, RPV, ducted fan, vertical takeoff. Includes bibliographical references (p. 74-75). Also available online.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, June 2009.
Thesis Advisor(s): Horne, Gary E. "June 2009." Description based on title screen as viewed on July 13, 2009. Author(s) subject terms: border security, border protection, border patrol, unmanned aerial system (UAS), UAV, MANA, Nearly-Orthogonal Latin Hypercube, regression tree, linear regression. Includes bibliographical references (p. 89-93). Also available in print.

A distributed actuation array was installed on a blended-wing-body uninhabited aerial vehicle and tested in the 12-foot subsonic wind tunnel at NASA?s Langley Research Center. From the results of these tests, a discussion is given of the baseline aircraft, its conventional control surfaces, and the distributed array. Each effector in the distributed array was tested individually as well as pre-determined configurations incorporating all 12 effectors on each wing. From the tests on the individual effectors, a method was created that allows for the prediction of the control authorities for any configuration of the array. The six pre-determined shapes served as bases for comparison to determine the accuracy of the prediction scheme. Additionally, the shapes were compared to the conventional control surfaces to determine if a distributed array could completely replace those control surfaces.

Approximately 20 years have passed now since the NTSB issued its original recommendation to expedite development, certification and production of low-cost proximity warning and conflict detection systems for general aviation [1]. While some systems are in place (TCAS [2]), ¡¨see-and-avoid¡¨ remains the primary means of separation between light aircrafts sharing the national airspace. The requirement for a collision avoidance or sense-and-avoid capability onboard unmanned aircraft has been identified by leading government, industry and regulatory bodies as one of the most significant challenges facing the routine operation of unmanned aerial systems (UAS) in the national airspace system (NAS) [3, 4]. In this thesis, we propose and develop a novel image-based collision avoidance system to detect and avoid an upcoming conflict scenario (with an intruder) without first estimating or filtering range. The proposed collision avoidance system (CAS) uses relative bearing ƒÛ and angular-area subtended ƒê , estimated from an image, to form a test statistic AS C . This test statistic is used in a thresholding technique to decide if a conflict scenario is imminent. If deemed necessary, the system will command the aircraft to perform a manoeuvre based on ƒÛ and constrained by the CAS sensor field-of-view. Through the use of a simulation environment where the UAS is mathematically modelled and a flight controller developed, we show that using Monte Carlo simulations a probability of a Mid Air Collision (MAC) MAC RR or a Near Mid Air Collision (NMAC) RiskRatio can be estimated. We also show the performance gain this system has over a simplified version (bearings-only ƒÛ ). This performance gain is demonstrated in the form of a standard operating characteristic curve. Finally, it is shown that the proposed CAS performs at a level comparable to current manned aviations equivalent level of safety (ELOS) expectations for Class E airspace. In some cases, the CAS may be oversensitive in manoeuvring the owncraft when not necessary, but this constitutes a more conservative and therefore safer, flying procedures in most instances.

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Submitted in partial fulfilment of the academic requirements for the Degree of Master of Technology: Mechanical Engineering, Durban Institute of Technology, 2004.
The study presented here addresses the design of the composite wing and canard structures for an -un-inh-ab-it-ed-combat air vehicle. The desian philosophy is based on a ~- combination of finite element analysis and mathematical programming. The wings and canards were manufactured using advanced composite materials. the manufacturing methodology was based on a rapid protoryping approach using 3D computer models and eNe machining. The theory of composite materials is covered in detail, attention IS given to the properties of the separate constituents, composite material properties and manufacturing methods that are relevant to the project. The finite element method and sequential linear programming are discussed in the context of structural analysis and optimisation. An overview of the methodology and how it is implemented is presented. Numerical optimisation techniques are discussed with particular emphasis being placed on sequential linear programming. The optimisation problem formulation is presented in detail with attention paid to elements and their formulation as well as design variables, constraints and sensitivity analysis. Two design concepts were considered for the wing and canard structures, the first being a conventional configuration and the second being a novel radial design. The development and evaluation of these structural concepts are presented in detail. The optimisation study done on the canard is also presented as well as the manufacture thereof. Details regarding the manufacturing methodology used in the construction of the canard for the uninhabited combat air vehicle are presented in detail with particular
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Thesis submitted in compliance with the requirements for the Master's Degree in Technology: Department of Mechanical Engineering, Durban University of Technology, 2008.
The development of an evolutionary optimisation method and its application to the design of an advanced composite structure is discussed in this study. Composite materials are increasingly being used in various fields, and so optimisation of such structures would be advantageous. From among the various methods available, one particular method, known as Evolutionary Structural Optimisation (ESO), is shown here. ESO is an empirical method, based on the concept of removing and adding material from a structure, in order to create an optimum shape. The objective of the research is to create an ESO method, utilising MSC.Patran/Nastran, to optimise composite structures. The creation of the ESO algorithm is shown, and the results of the development of the ESO algorithm are presented. A tailfin of an aircraft was used as an application example. The aim was to reduce weight and create an optimised design for manufacture. The criterion for the analyses undertaken was stress based. Two models of the tailfin are used to demonstrate the effectiveness of the developed ESO algorithm. The results of this research are presented in the study.

碩士
淡江大學
航空太空工程學系碩士班
94
The optimal trajectories of solar powered Uninhabitant Aerial Vehicle (UAV) flying in atmosphere are studied. The solar powered UAV will not expel the fuel during the flight. Therefore its mass keeps constant during the flight. The energy loss does not affect the motion of the vehicle explicitly. The optimal control law for level turn is obtained by considering the energy as the performance index. The result control law contains state variables only which can be easily implemented. The optimal trajectories for various final heading angles and spiral mission are presented as examples. The optimal climbing trajectory is obtained by keeping the lift control at optimal lift-to-drag ratio. By combining the guidance laws of optimal level turn and climbing, we can design the optimal three-dimension trajectories.

碩士
淡江大學
航空太空工程學系碩士班
96
The thesis is to design a tailless UAV and its guidance, navgation and autopilot systems. Procedure of UAV design uses standard aircraft design procedure which includes concept design, preliminary design and detail design. The configuration and structure of UAV depend on the performance reqirements. Attitude control uses state feedback control and LQ criterion to design control gain. The MATLAB® is implemented to simulate the control responses. The ARM® and PIC® microcontrollers are used to build up the avionics and ground control station.

Rapidly evolving technologies in the autonomous operation of Uninhabited Aerial Vehicles (UAVs) and associated developments in low-cost sensors have created significant interest among researchers in using them for various civil and military applications. With the autonomy and presence of various sensing equipment, onboard UAVs lead to problems in the privacy, safety, and security of many safety-critical infrastructures. A critical infrastructure that needs to be protected is approximated by the convex region and called territory. A team of UAVs that protects the territory is called the defenders and UAVs which try to enter the territory are called the intruders. A team of defenders operates inside and, on the perimeter, and protects the territory from intruders by capturing intruders on the perimeter is referred as the Perimeter Defense Problem (PDP). The velocity of intruders is used to predict the arrival location on the perimeter and arrival time. In this way, each intruder generates a spatio-temporal task for the defenders to reach tha= t specific location at a specific time to neutralize that intruder. So, PDP is formulated as the spatio-temporal multi-task assignment (STMTA) problem. In the STMTA problem, some minimum number of defenders (robots) are required to execute the given spatio-temporal tasks; without this minimum number of defenders, STMTA problem is ill-posed. The proposed Dynamic REsource Allocation with Multi-task assignment (DREAM) algorithm solves the bottleneck issue of iterative computation for the required number of robots and provides the two-step solution to compute the required minimum number of robots and their optimal assignments to execute given spatio-temporal tasks. Next, the trajectory generation algorithm has been developed to compute the trajectory of each defender. Furthermore, it is proved that all the computed trajectories of homogeneous agents, operating in the convex region, are collision-free. For highly maneuvering intruders, the errors in the prediction of tasks deteriorate the performance of DREAM. In the P-DREAM approach, a dedicated defender is assigned to each prioritized intruder by enforcing the prioritized intruder as a first task. A prioritized intruder must be delegated to the reserve defender before it becomes infeasible for the reserve defender. The static design for PDP computes the minimum number of reserve stations, their optimal location, priority region, monitoring region, and the minimum number of defenders required for monitoring. The quantification of priority and monitoring region will be helpful in practical implementations. For protecting a large territory, more defenders are required, also each defender has a limited sensing range to detect and track intruders. To address these issues of partial observability and scalability the decentralized spatio-temporal multi-task assignment approach is proposed. A modified consensus-based bundle algorithm has been proposed to solve the STMTA problem. Finally, the thesis demonstrates the working of the DREAM approach for heterogeneous pick-up and just-in-time delivery (PJITD) problems. Just-in-time tasks have been used to improve operational efficacy for static (priorly known) tasks. The non-iterative solution of modified DREAM overcomes the bottleneck problem of the iterative (and hence offline) solution and provides a real-time implementable solution. The cost function is modified to include the traveling time, operating time, and heterogeneous skills required to execute the tasks. The working of modified DREAM is illustrated using high-fidelity ROS2-GAZEBO simulations and lab-scale hardware experiments.