Spelling suggestions: "subject:"unmanned aircraft"" "subject:"unmanned ircraft""
71 |
Small-Target Detection and Observation with Vision-Enabled Fixed-Wing Unmanned Aircraft SystemsMorgan, Hayden Matthew 27 May 2021 (has links)
This thesis focuses on vision-based detection and observation of small, slow-moving targets using a gimballed fixed-wing unmanned aircraft system (UAS). Generally, visual tracking algorithms are tuned to detect motion of relatively large objects in the scene with noticeably significant motion; therefore, applications such as high-altitude visual searches for human motion often ignore target motion as noise. Furthermore, after a target is identified, arbitrary maneuvers for transitioning to overhead orbits for better observation may result in temporary or permanent loss of target visibility. We present guidelines for tuning parameters of the Visual Multiple Target Tracking (Visual MTT) algorithm to enhance its detection capabilities for very small, slow-moving targets in high-resolution images. We show that the tuning approach is able to detect walking motion of a human described by 10-15 pixels from high altitudes. An algorithm is then presented for defining rotational bounds on the controllable degrees of freedom of an aircraft and gimballed camera system for maintaining visibility of a known ground target. Critical rotations associated with the fastest loss or acquisition of target visibility are also defined. The accuracy of these bounds are demonstrated in simulation and simple applications of the algorithm are described for UAS. We also present a path planning and control framework for defining and following both dynamically and visually feasibly transition trajectories from an arbitrary point to an orbit over a known target for further observation. We demonstrate the effectiveness of this framework in maintaining constant target visibility while transitioning to the intended orbit as well as in transitioning to a lower altitude orbit for more detailed visual analysis of the intended target.
|
72 |
EXPLORING THE STATE OF SMS PRACTICES FOR COMMERCIAL UAS OPERATIONS AT AIRPORTSPratik Jadhav (12456546) 25 April 2022 (has links)
<p>Safety Management Systems (SMS) in the aviation industry is increasingly an essential aspect of identifying hazards and managing the associated risks. While SMS has become commonplace and is often a regulatory requirement for air carriers, it remains voluntary for many other aviation service providers such as airports. Over the past decade, commercial UAS operations have significantly increased, leading to safety and economic challenges for airports. This research studied the current state of SMS and commercial UAS operations at airports. This research utilized a mix of quantitative and qualitative methods, which included an extensive literature review, interviews, and a survey of airport stakeholders. The literature review confirmed an increase in UAS hazards and risks within the airport operating area coupled with immature SMS practices that address these UAS operations. To build on the findings from the review of literature, a survey instrument was developed, distributed to airport stakeholders, and the responses were statistically analyzed. To gain greater insight into these findings, researchers interviewed three airport subject matter experts. The study compared the airports current state of SMS with UAS operations, the airport stakeholder’s level of familiarity with related policies, and their need for additional UAS SMS guidance material or training. Research results suggest a need for further development and adoption of robust SMS practices at airports along with education and training. This study may assist airport stakeholders, UAS operators, and regulators to further develop robust safety and risk management practices that support safe UAS operations within the airport operating area.</p>
|
73 |
Selected Aspects of Navigation and Path Planning in Unmanned Aircraft SystemsWzorek, Mariusz January 2011 (has links)
Unmanned aircraft systems (UASs) are an important future technology with early generations already being used in many areas of application encompassing both military and civilian domains. This thesis proposes a number of integration techniques for combining control-based navigation with more abstract path planning functionality for UASs. These techniques are empirically tested and validated using an RMAX helicopter platform used in the UASTechLab at Linköping University. Although the thesis focuses on helicopter platforms, the techniques are generic in nature and can be used in other robotic systems. At the control level a navigation task is executed by a set of control modes. A framework based on the abstraction of hierarchical concurrent state machines for the design and development of hybrid control systems is presented. The framework is used to specify reactive behaviors and for sequentialisation of control modes. Selected examples of control systems deployed on UASs are presented. Collision-free paths executed at the control level are generated by path planning algorithms.We propose a path replanning framework extending the existing path planners to allow dynamic repair of flight paths when new obstacles or no-fly zones obstructing the current flight path are detected. Additionally, a novel approach to selecting the best path repair strategy based on machine learning technique is presented. A prerequisite for a safe navigation in a real-world environment is an accurate geometrical model. As a step towards building accurate 3D models onboard UASs initial work on the integration of a laser range finder with a helicopter platform is also presented. Combination of the techniques presented provides another step towards building comprehensive and robust navigation systems for future UASs.
|
74 |
Dynamic Probabilistic Risk Assessment of Autonomous Vehicle SystemsHejase, Mohammad 28 August 2019 (has links)
No description available.
|
75 |
On Integral Quadratic Constraint Theory and Robust Control of Unmanned Aircraft SystemsFry, Jedediah Micah 11 September 2019 (has links)
This dissertation advances tools for the certification of unmanned aircraft system (UAS) flight controllers. We develop two thrusts to this goal: (1) the validation and improvement of an uncertain UAS framework based on integral quadratic constraint (IQC) theory and (2) the development of novel IQC theorems which allow the analysis of uncertain systems having time-varying characteristics.
Pertaining to the first thrust, this work improves and implements an IQC-based robustness analysis framework for UAS. The approach models the UAS using a linear fractional transformation on uncertainties and conducts robustness analysis on the uncertain system via IQC theory. By expressing the set of desired UAS flight paths with an uncertainty, the framework enables analysis of the uncertain UAS flying about any level path whose radius of curvature is bounded. To demonstrate the versatility of this technique, we use IQC analysis to tune trajectory-tracking and path-following controllers designed via H2 or H-infinity synthesis methods. IQC analysis is also used to tune path-following PID controllers. By employing a non-deterministic simulation environment and conducting numerous flight tests, we demonstrate the capability of the framework in predicting loss of control, comparing the robustness of different controllers, and tuning controllers. Finally, this work demonstrates that signal IQCs have an important role in obtaining IQC analysis results which are less conservative and more consistent with observations from flight test data.
With regards to the second thrust, we prove a novel theorem which enables robustness analysis of uncertain systems where the nominal plant and the IQC multiplier are linear time-varying systems and the nominal plant may have a non-zero initial condition. When the nominal plant and the IQC multiplier are eventually periodic, robustness analysis can be accomplished by solving a finite-dimensional semidefinite program. Time-varying IQC multipliers are beneficial in analysis because they provide the possibility of reducing conservatism and are capable of expressing uncertainties that have unique time-domain characteristics. A number of time-varying IQC multipliers are introduced to better describe such uncertainties. The utility of this theorem is demonstrated with various examples, including one which produces bounds on the UAS position after an aggressive Split-S maneuver. / Doctor of Philosophy / This work develops tools to aid in the certification of unmanned aircraft system (UAS) flight controllers. The forthcoming results are founded on robust control theory, which allows the incorporation of a variety of uncertainties in the UAS mathematical model and provides tools to determine how robust the system is to these uncertainties. Such a foundation provides a complementary perspective to that obtained with simulations. Whereas simulation environments provide a probabilistic-type analysis and are oftentimes costly, the following results provide worst-case guarantees—for the allowable disturbances and uncertainties—and require far less computational resources. Here we take two approaches in our development of certification tools for UAS. First we validate and improve on an uncertain UAS framework that relies on integral quadratic constraint (IQC) theory to analyze the robustness of the UAS in the presence of uncertainties and disturbances. Our second approach develops novel IQC theorems that can aid in providing bounds on the UAS state during its flight trajectory. Though the applications in this dissertation are focused on UAS, the theory can be applied to a wide variety of physical and nonphysical problems wherein uncertainties in the mathematical model cannot be avoided.
|
76 |
Integration of a Complete Detect and Avoid System for Small Unmanned Aircraft SystemsWikle, Jared Kevin 01 May 2017 (has links)
For unmanned aircraft systems to gain full access to the National Airspace System (NAS), they must have the capability to detect and avoid other aircraft. This research focuses on the development of a detect-and-avoid (DAA) system for small unmanned aircraft systems. To safely avoid another aircraft, an unmanned aircraft must detect the intruder aircraft with ample time and distance. Two analytical methods for finding the minimum detection range needed are described. The first method, time-based geometric velocity vectors (TGVV), includes the bank-angle dynamics of the ownship while the second, geometric velocity vectors (GVV), assumes an instantaneous bank-angle maneuver. The solution using the first method must be found numerically, while the second has a closed-form analytical solution. These methods are compared to two existing methods. Results show the time-based geometric velocity vectors approach is precise, and the geometric velocity vectors approach is a good approximation under many conditions. The DAA problem requires the use of a robust target detection and tracking algorithm for tracking multiple maneuvering aircraft in the presence of noisy, cluttered, and missed measurements. Additionally these algorithms needs to be able to detect overtaking intruders, which has been resolved by using multiple radar sensors around the aircraft. To achieve these goals the formulation of a nonlinear extension to R-RANSAC has been performed, known as extended recursive-RANSAC (ER-RANSAC). The primary modifications needed for this ER-RANSAC implementation include the use of an EKF, nonlinear inlier functions, and the Gauss-Newton method for model hypothesis and generation. A fully functional DAA system includes target detection and tracking, collision detection, and collision avoidance. In this research we demonstrate the integration of each of the DAA-system subcomponents into fully functional simulation and hardware implementations using a ground-based radar setup. This integration resulted in various modifications of the radar DSP, collision detection, and collision avoidance algorithms, to improve the performance of the fully integrated DAA system. Using these subcomponents we present flight results of a complete ground-based radar DAA system, using actual radar hardware.
|
77 |
Airborne Collision Detection and Avoidance for Small UAS Sense and Avoid SystemsSahawneh, Laith Rasmi 01 January 2016 (has links)
The increasing demand to integrate unmanned aircraft systems (UAS) into the national airspace is motivated by the rapid growth of the UAS industry, especially small UAS weighing less than 55 pounds. Their use however has been limited by the Federal Aviation Administration regulations due to collision risk they pose, safety and regulatory concerns. Therefore, before civil aviation authorities can approve routine UAS flight operations, UAS must be equipped with sense-and-avoid technology comparable to the see-and-avoid requirements for manned aircraft. The sense-and-avoid problem includes several important aspects including regulatory and system-level requirements, design specifications and performance standards, intruder detecting and tracking, collision risk assessment, and finally path planning and collision avoidance. In this dissertation, our primary focus is on developing an collision detection, risk assessment and avoidance framework that is computationally affordable and suitable to run on-board small UAS. To begin with, we address the minimum sensing range for the sense-and-avoid (SAA) system. We present an approximate close form analytical solution to compute the minimum sensing range to safely avoid an imminent collision. The approach is then demonstrated using a radar sensor prototype that achieves the required minimum sensing range. In the area of collision risk assessment and collision prediction, we present two approaches to estimate the collision risk of an encounter scenario. The first is a deterministic approach similar to those been developed for Traffic Alert and Collision Avoidance (TCAS) in manned aviation. We extend the approach to account for uncertainties of state estimates by deriving an analytic expression to propagate the error variance using Taylor series approximation. To address unanticipated intruders maneuvers, we propose an innovative probabilistic approach to quantify likely intruder trajectories and estimate the probability of collision risk using the uncorrelated encounter model (UEM) developed by MIT Lincoln Laboratory. We evaluate the proposed approach using Monte Carlo simulations and compare the performance with linearly extrapolated collision detection logic. For the path planning and collision avoidance part, we present multiple reactive path planning algorithms. We first propose a collision avoidance algorithm based on a simulated chain that responds to a virtual force field produced by encountering intruders. The key feature of the proposed approach is to model the future motion of both the intruder and the ownship using a chain of waypoints that are equally spaced in time. This timing information is used to continuously re-plan paths that minimize the probability of collision. Second, we present an innovative collision avoidance logic using an ownship centered coordinate system. The technique builds a graph in the local-level frame and uses the Dijkstra's algorithm to find the least cost path. An advantage of this approach is that collision avoidance is inherently a local phenomenon and can be more naturally represented in the local coordinates than the global coordinates. Finally, we propose a two step path planner for ground-based SAA systems. In the first step, an initial suboptimal path is generated using A* search. In the second step, using the A* solution as an initial condition, a chain of unit masses connected by springs and dampers evolves in a simulated force field. The chain is described by a set of ordinary differential equations that is driven by virtual forces to find the steady-state equilibrium. The simulation results show that the proposed approach produces collision-free plans while minimizing the path length. To move towards a deployable system, we apply collision detection and avoidance techniques to a variety of simulation and sensor modalities including camera, radar and ADS-B along with suitable tracking schemes.
|
78 |
Magnetic signature characterization of a fixed-wing vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV)Hansen, Cody Robert Daniel 17 December 2018 (has links)
The use of magnetometers combined with unmanned aerial vehicles (UAVs) is an emerging market for commercial and military applications. This study presents the methodology used to magnetically characterize a novel fixed-wing vertical take-off and landing (VTOL) UAV. The most challenging aspect of integrating magnetometers on manned or unmanned aircraft is minimizing the amount of magnetic noise generated by the aircraft’s onboard components. As magnetometer technology has improved in recent years magnetometer payloads have decreased in size. As a result, there has been an increase in opportunities to employ small to medium UAV with magnetometer applications. However, in comparison to manned aviation, small UAVs have smaller distance scales between sources of interference and sensors. Therefore, more robust magnetic characterization techniques are required specifically for UAVs. This characterization determined the most suitable position for the magnetometer payload by evaluating the aircraft’s static-field magnetic signature. For each aircraft component, the permanent and induced magnetic dipole moment characteristics were determined experimentally. These dipole characteristics were used to build three dimensional magnetic models of the aircraft. By assembling the dipoles in 3D space, analytical and numerical static-field solutions were obtained using MATLAB computational and COMSOL finite element analysis frameworks. Finally, Tolles and Lawson aeromagnetic compensation coefficients were computed and compared to evaluate the maneuver noise for various payload locations. The magnetic models were used to study the sensitivity of the aircraft configuration and to simultaneously predict the effects at potential sensor locations. The study concluded by predicting that a wingtip location was the area of lowest magnetic interference. / Graduate
|
79 |
Integration and assessment of a dual core chip - Atmel’s DIOPSIS 940 - for a flight control system.Majewski, Łukasz January 2009 (has links)
A dual core Atmel DIOPSIS 940 chip consists of a DSP and an ARM9 functional units in a single silicon die. This thesis presents the process of integration and assessment of using this processor in a flight control system. A complete design of the system is provided including a description of the DIOPSIS 940 from the perspective of requirements of the application. The integration of the processor with a typical set of components of a flight control system is provided. Additionally, a suite of programs required for developing software for the system is included. Capabilities of both cores of the processor are analysed in a series of experiments. Computational performance in typical tasks of a flight control system is analyzed and compared. The application of attitude stabilization for a micro-scale UAS is described.
|
80 |
Možnosti rozvoje a zajištění bezpečnosti dálkově řízených letadel (RPAS) v ČR / Development opportunities and ensure the safety of remote-controlled aircraft (RPAS) in Czech RepublicHabrnal, Lukáš January 2015 (has links)
Tato diplomová práce se zabývá možnostmi rozvoje a zajištěním bezpečnosti dálkově řízených letadel (RPAS) v ČR. Práce je rozdělena do 3 hlavních částí: legislativní, technické a bezpečnostní. V legislativní části najdeme současné a připravované předpisy pro RPAS. Technická část popisuje vývoj bezpilotního letectví až k dnešním civilním RPAS, které jsou popsány na příkladech používaných v ČR. V poslední části je věnován prostor oblastem, které, především z bezpečnostního hlediska, omezují rozvoj RPAS.
|
Page generated in 0.0368 seconds