Air Force Institute of Technology Research Report 2019

This Research Report presents the FY19 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document

Air Force Institute of Technology Research Report 2020

This Research Report presents the FY20 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document

Air Force Institute of Technology Research Report 2016

This Research Report presents the FY16 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs)

Real-time probabilistic collision avoidance for autonomous vehicles, using order reductive conflict metrics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2003.Includes bibliographical references (p. 131-137).Contemporary collision avoidance systems such as the Traffic Alert and Collision Avoidance System (TCAS) have proven their effectiveness in the Commercial Aviation (CA) industry within the last decade. Yet, TCAS and many systems like it represent attempts at collision avoidance that do not fully recognize the uncertain nature of a conflict event. Most systems circumvent probabilistic representation through simplifying approximations and pre-compiled notions of hazard space, since probabilistic representation of collision in three dimensions is considered to be an intractable problem. Recent developments by Kuchar and Yang[70] and Paielli and Erzberger[50] have shown that collision avoidance may be cast as a probabilistic state-space problem. Innovative solution approaches may then allow systems of this nature to probe collision risk in real-time, based on real-time state estimates. The research documented in this thesis further develops the probabilistic approach for the non-cooperative, two-vehicle problem as applied in real-time to autonomous aircraft. The research is kept in a general form, thereby warranting application to a wide variety of multi-dimensional collision avoidance applications and scenario geometries. The work primarily improves the state of the art through the creation of order reductive collision metrics in order to simplify the intractable problem of multi-dimensional collision risk calculation. As a result, a tractable, real-time, probabilistic algorithm is developed for the calculation of collision risk as a function of time.(cont.) The collision avoidance problem is contextualized not only within the realm of recent research within the CA industry, but is also likened to such concepts as the first passage time problem encountered in physics, and the field of reliability theory often encountered in civil and mechanical engineering problems. Yang's method of solution, a piece-wise straight-line Monte-Carlo approach to state propagation, is extended with a model-predictive, finite horizon risk accumulation algorithm. Through this extension we are capable of modelling collision risk for linear(-ized), time-variant, dynamic vehicle models and control strategies. A strategy is developed whereby the advantage of delayed collision avoidance action is calculated and it is framed as an extension of the notion of system operating characteristics (SOCs). The complexity of the probabilistic representation is reduced by application of quadratic conflict metrics. The numerical complexity can be reduced from [Omicron](N2n) to [Omicron](Nlog2(N)) at each time step within a finite horizon time interval. Risk calculation errors due to numerical and stochastic approximations are quantified. An applicability test is also devised whereby a vehicle's dynamic model and control characteristics may be used to calculate risk error estimates before implementing the bulk of the algorithmic solution. Various other applications of the work, outside the scope of collision avoidance, are also identified.by Thomas Jones.Ph.D

Outdoor operations of multiple quadrotors in windy environment

Coordinated multiple small unmanned aerial vehicles (sUAVs) offer several advantages over a single sUAV platform. These advantages include improved task efficiency, reduced task completion time, improved fault tolerance, and higher task flexibility. However, their deployment in an outdoor environment is challenging due to the presence of wind gusts. The coordinated motion of a multi-sUAV system in the presence of wind disturbances is a challenging problem when considering collision avoidance (safety), scalability, and communication connectivity. Performing wind-agnostic motion planning for sUAVs may produce a sizeable cross-track error if the wind on the planned route leads to actuator saturation. In a multi-sUAV system, each sUAV has to locally counter the wind disturbance while maintaining the safety of the system. Such continuous manipulation of the control effort for multiple sUAVs under uncertain environmental conditions is computationally taxing and can lead to reduced efficiency and safety concerns. Additionally, modern day sUAV systems are susceptible to cyberattacks due to their use of commercial wireless communication infrastructure. This dissertation aims to address these multi-faceted challenges related to the operation of outdoor rotor-based multi-sUAV systems. A comprehensive review of four representative techniques to measure and estimate wind speed and direction using rotor-based sUAVs is discussed. After developing a clear understanding of the role wind gusts play in quadrotor motion, two decentralized motion planners for a multi-quadrotor system are implemented and experimentally evaluated in the presence of wind disturbances. The first planner is rooted in the reinforcement learning (RL) technique of state-action-reward-state-action (SARSA) to provide generalized path plans in the presence of wind disturbances. While this planner provides feasible trajectories for the quadrotors, it does not provide guarantees of collision avoidance. The second planner implements a receding horizon (RH) mixed-integer nonlinear programming (MINLP) model that is integrated with control barrier functions (CBFs) to guarantee collision-free transit of the multiple quadrotors in the presence of wind disturbances. Finally, a novel communication protocol using Ethereum blockchain-based smart contracts is presented to address the challenge of secure wireless communication. The U.S. sUAV market is expected to be worth $92 Billion by 2030. The Association for Unmanned Vehicle Systems International (AUVSI) noted in its seminal economic report that UAVs would be responsible for creating 100,000 jobs by 2025 in the U.S. The rapid proliferation of drone technology in various applications has led to an increasing need for professionals skilled in sUAV piloting, designing, fabricating, repairing, and programming. Engineering educators have recognized this demand for certified sUAV professionals. This dissertation aims to address this growing sUAV-market need by evaluating two active learning-based instructional approaches designed for undergraduate sUAV education. The two approaches leverages the interactive-constructive-active-passive (ICAP) framework of engagement and explores the use of Competition based Learning (CBL) and Project based Learning (PBL). The CBL approach is implemented through a drone building and piloting competition that featured 97 students from undergraduate and graduate programs at NJIT. The competition focused on 1) drone assembly, testing, and validation using commercial off-the-shelf (COTS) parts, 2) simulation of drone flight missions, and 3) manual and semi-autonomous drone piloting were implemented. The effective student learning experience from this competition served as the basis of a new undergraduate course on drone science fundamentals at NJIT. This undergraduate course focused on the three foundational pillars of drone careers: 1) drone programming using Python, 2) designing and fabricating drones using Computer-Aided Design (CAD) and rapid prototyping, and 3) the US Federal Aviation Administration (FAA) Part 107 Commercial small Unmanned Aerial Vehicles (sUAVs) pilot test. Multiple assessment methods are applied to examine the students’ gains in sUAV skills and knowledge and student attitudes towards an active learning-based approach for sUAV education. The use of active learning techniques to address these challenges lead to meaningful student engagement and positive gains in the learning outcomes as indicated by quantitative and qualitative assessments

Design and implementation of a reliable unmanned aerial system design

With the increase in popularity of the UAV, due to their high accessibility, it becomes even more important that they can be operated in a safe way not only to protect the UAV but also to protect the surroundings and the people. This thesis has the main objective to study ways that allow to increase the security of UAV operations. We start by identifying the failures and their impact and proceed to develop a module that is independent from the principal modules of the UAV. Within this work we opted to focus on the implementation of detection and avoidance of obstacles for the MAV type of UAVs. After making an evaluation of different types of ultrasonic sensors we studied ways to connect them in an array and get a 360º cover of the UAV. Then, we developed three different implementations of an object detection algorithm, with each algorithm being a more complex version of the previous one: First Algorithm – Detection and distance estimation from an object Second Algorithm – Added a false alarm avoidance and direction estimation of the object Third Algorithm – Added the ability to detect more than one object Following the evaluation of those algorithms, we then aimed to develop an interface for the collision module which could send a message to the UAV if an object was detected so that it can change its flight mode and prevent collision. For that the MAVlink protocol was selected since it is compatible with a lot of flight controllers. In the end a final study was made in order to check what was the maximum velocity that an UAV can achieve in order for it to react in time to avoid collision.Com o aumento na popularidade dos veículos aéreos não-tribulados, devido à sua elevada acessibilidade, torna-se cada vez mais importante quando se usa um UAV que ele esteja seguro não só para proteger o UAV mas também para proteger as pessoas e os redores de onde é usado. Esta tese tem o objetivo principal de estudar as diferentes maneiras de aumentar a segurança dos UAV quando está em uso. Começamos por identificar as várias falhas e o seu impacto e quando terminamos isso procedemos a desenvolver um módulo que é independente do módulo principal do UAV. Com os estudos feitos optamos por focar na implementação de deteção e evitação de obstáculos e adaptar isso para os UAVs do tipo MAV. Depois da avaliação sobre os diferentes tipos de sensores ultrassónicos foi estudado várias maneiras de os ligar em sequência e conseguir uma cobertura de 360º no UAV. Depois nos desenvolvemos três diferentes implementações de um algoritmo de deteção de obstáculos, em que cada um desses algoritmos era uma versão mais complexa do anterior: Primeiro Algoritmo – Deteção e estimação da distância de um objeto. Segundo Algoritmo – Adição da evitação do falso alarme e estimação da direção do objeto Terceiro Algoritmo – Adição da habilidade de detetar mais do que um objeto Após a avaliação destes algoritmos, foi desenvolvida uma interface para o módulo de evitação da colisão com obstáculos que conseguia mandar uma mensagem para o UAV para o caso em que um objeto foi detetado, para ele mudar o modo de voo e assim evitar a colisão com o obstáculo. Para isso selecionou-se o protocolo MAVlink devido à sua compatibilidade com muitos dos modos de voo. Um estudo final foi realizado de modo a verificar qual seria a velocidade máxima que um UAV poderia ter de modo a conseguir reagir a tempo e evitar a colisão

A framework for modeling and simulation of control, navigation, and surveillance for unmanned aircraft separation assurance

The integration of Unmanned Aircraft Systems in the National Airspace System (UASNAS) problem has received much attention because of the growing number of variety of mission types and the rapid growth of UAS market. Among the many challenging UASNAS problems, separation assurance is considered to be particularly complex, having many interactions among the elements in different levels of abstraction and coupling effects between the different disciplinary domains. In order to explore the separation assurance problem, an analytic model should capture diverse operational scenarios, vehicle dynamics, and subsystem functions such as sensor/surveillance, control, navigation and communications. This has major implications on the analytic model requirements, especially in regard to modeling scope, resolution (or fidelity), and computational expense. The objective of this thesis is to formulate and demonstrate improvements in modeling and simulation of fully integrated UAS to enable systems analysis across the levels of abstraction and multiple disciplines. This work also quantitatively characterizes collision avoidance as a critical element of separation assurance in terms of system behaviors across the levels of abstraction and multiple disciplines. To address these objectives, this thesis contributes to four areas: (1) a statistical gain-scheduling method to improve computational efficiency without a loss of accuracy or fidelity, (2) a hybrid collision avoidance algorithm using a machine learning technique that improves computational runtime as well as optimal trajectory cost, (3) a two-layer obstacle avoidance algorithm for a multi-obstacle environment, (4) a rapid, data-driven and grid-based urban modeling methodology using airborne LiDAR sources. The proposed modeling and simulation capability provides insights into the interaction between system of systems, systems, and subsystems that cannot be characterized by a conventional modeling and simulation environment. To illustrate the collision avoidance problem, this thesis examines the navigation of a fixed wing UAV in a dense urban environment.Ph.D