Navigation, Guidance, Control and Dynamics Commons^™

Immersive Framework For Designing Trajectories Using Augmented Reality, Joseph Anderson, Leo Materne, Karis Cooks, Michelle Aros, Jaia Huggins, Jesika Geliga-Torres, Kamden Kuykendall, David Canales, Barbara Chaparro

Publications

The intuitive interaction capabilities of augmented reality make it ideal for solving complex 3D problems that require complex spatial representations, which is key for astrodynamics and space mission planning. By implementing common and complex orbital mechanics algorithms in augmented reality, a hands-on method for designing orbit solutions and spacecraft missions is created. This effort explores the aforementioned implementation with the Microsoft Hololens 2 as well as its applications in industry and academia. Furthermore, a human-centered design process and study are utilized to ensure the tool is user-friendly while maintaining accuracy and applicability to higher-fidelity problems.

Deep-Learning Based Multiple-Model Bayesian Architecture For Spacecraft Fault Estimation, Rocio Jado Puente

Doctoral Dissertations and Master's Theses

This thesis presents recent findings regarding the performance of an intelligent architecture designed for spacecraft fault estimation. The approach incorporates a collection of systematically organized autoencoders within a Bayesian framework, enabling early detection and classification of various spacecraft faults such as reaction-wheel damage, sensor faults, and power system degradation.

To assess the effectiveness of this architecture, a range of performance metrics is employed. Through extensive numerical simulations and in-lab experimental testing utilizing a dedicated spacecraft testbed, the capabilities and accuracy of the proposed intelligent architecture are analyzed. These evaluations provide valuable insights into the architecture's ability to detect and classify …

Verification And Validation Of Robot Manipulator Adaptive Control With Actuator Deficiency, Sebastian Comeaux

Doctoral Dissertations and Master's Theses

This work addresses the joint tracking problem of robotic manipulators with uncertain dynamical parameters and actuator deficiencies, in the form of an uncertain control effectiveness matrix, through adaptive control design, simulation, and experimentation. Specifically, two novel adaptive controller formulations are implemented and tested via simulation and experimentation. The proposed adaptive control formulations are designed to compensate for uncertainties in the dynamical system parameters as well as uncertainties in the control effectiveness matrix that pre-multiplies the control input. The uncertainty compensation of the dynamical parameters is achieved via the use of the desired model compensation–based adaptation, while the uncertainties related to …

Artificial Intelligence-Assisted Inertial Geomagnetic Passive Navigation, Andrei Cuenca

Doctoral Dissertations and Master's Theses

In recent years, the integration of machine learning techniques into navigation systems has garnered significant interest due to their potential to improve estimation accuracy and system robustness. This doctoral dissertation investigates the use of Deep Learning combined with a Rao-Blackwellized Particle Filter for enhancing geomagnetic navigation in airborne simulated missions.

A simulation framework is developed to facilitate the evaluation of the proposed navigation system. This framework includes a detailed aircraft model, a mathematical representation of the Earth's magnetic field, and the incorporation of real-world magnetic field data obtained from online databases. The setup allows an accurate assessment of the performance …

Safe Navigation Of Quadruped Robots Using Density Functions, Andrew Zheng

All Theses

Safe navigation of mission-critical systems is of utmost importance in many modern autonomous applications. Over the past decades, the approach to the problem has consisted of using probabilistic methods, such as sample-based planners, to generate feasible, safe solutions to the navigation problem. However, these methods use iterative safety checks to guarantee the safety of the system, which can become quite complex. The navigation problem can also be solved in feedback form using potential field methods. Navigation function, a class of potential field methods, is an analytical control design to give almost everywhere convergence properties, but under certain topological constraints and …

Kwad - Ksu All Weather Autonomous Drone, Nick Farinacci, Sebastian Gomez, Stewart Baker, Ed Sheridan

Symposium of Student Scholars

"KWAD" or "KSU all-Weather Autonomous Drone" project was sponsored by Ultool, LLC to the KSU Research and Service Foundation to create a lightweight drone capable of capturing HD video during all-weather operations. The conditions of all-weather operation include rainfall of one inch per hour and wind speeds of up to twenty miles per hour. In addition, a global minimum structural safety factor of two is required to ensure the system's integrity in extreme weather conditions. Potential mission profiles include autonomous aerial delivery, topological mapping in high moisture areas, security surveillance, search and rescue operations, emergency transportation of medical supplies, and …

Six-Degree-Of-Freedom Optimal Feedback Control Of Pinpoint Landing Using Deep Neural Networks, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua

Student Works

Machine learning regression techniques have shown success at feedback control to perform near-optimal pinpoint landings for low fidelity formulations (e.g. 3 degree-of-freedom). Trajectories from these low-fidelity landing formulations have been used in imitation learning techniques to train deep neural network policies to replicate these optimal landings in closed loop. This study details the development of a near-optimal, neural network feedback controller for a 6 degree-of-freedom pinpoint landing system. To model disturbances, the problem is cast as either a multi-phase optimal control problem or a triple single-phase optimal control problem to generate examples of optimal control through the presence of disturbances. …

Exploring Underwater Noise Issues: A Study Of Decentralized Approach, Takanori Uzumaki

World Maritime University Dissertations

No abstract provided.

Stability Of Deep Neural Networks For Feedback-Optimal Pinpoint Landings, Omkar S. Mulekar, Hancheol Cho, Riccardo Bevilacqua

Student Works

The ability to certify systems driven by neural networks is crucial for future rollouts of machine learning technologies in aerospace applications. In this study, the neural networks are used to represent a fuel-optimal feedback controller for two different 3-degree-of-freedom pinpoint landing problems. It is shown that the standard sum-ofsquares Lyapunov candidate is too restrictive to assess the stability of systems with fuel-optimal control profiles. Instead, a parametric Lyapunov candidate (i.e. a neural network) can be trained to sufficiently evaluate the closed-loop stability of fuel-optimal control profiles. Then, a stability-constrained imitation learning method is applied, which simultaneously trains a neural network …

Online Aircraft System Identification Using A Novel Parameter Informed Reinforcement Learning Method, Nathan Schaff

Doctoral Dissertations and Master's Theses

This thesis presents the development and analysis of a novel method for training reinforcement learning neural networks for online aircraft system identification of multiple similar linear systems, such as all fixed wing aircraft. This approach, termed Parameter Informed Reinforcement Learning (PIRL), dictates that reinforcement learning neural networks should be trained using input and output trajectory/history data as is convention; however, the PIRL method also includes any known and relevant aircraft parameters, such as airspeed, altitude, center of gravity location and/or others. Through this, the PIRL Agent is better suited to identify novel/test-set aircraft.

First, the PIRL method is applied to …

Rigid Body Constrained Motion Optimization And Control On Lie Groups And Their Tangent Bundles, Brennan S. Mccann

Doctoral Dissertations and Master's Theses

Rigid body motion requires formulations where rotational and translational motion are accounted for appropriately. Two Lie groups, the special orthogonal group SO(3) and the space of quaternions H, are commonly used to represent attitude. When considering rigid body pose, that is spacecraft position and attitude, the special Euclidean group SE(3) and the space of dual quaternions DH are frequently utilized. All these groups are Lie groups and Riemannian manifolds, and these identifications have profound implications for dynamics and controls. The trajectory optimization and optimal control problem on Riemannian manifolds presents significant opportunities for theoretical development. Riemannian optimization is an attractive …

Hardware-In-The-Loop Reaction Wheel Testbed With Camera Vision, Abigail Romero, Harvey Perkins, Stephen Kwok-Choon

College of Engineering Summer Undergraduate Research Program

Reaction wheels are widely used in aerospace systems as a method of attitude control. This research was focused on the design, development, and testing of a hardware-in-the-loop reaction wheel testbed that can be used for research and teaching applications related to satellite navigation and control. This project successfully utilized commercial off-the-shelf components to develop a reaction wheel capable of controlling the orientation of a freely rotating platform, as well as tracking objects using computer vision.

Design And Implementation Of A Launching Method For Free To Oscillate Dynamic Stability Testing, Kristen M. Carey

Mechanical & Aerospace Engineering Theses & Dissertations

Magnetic Suspension and Balance Systems (MSBS) allow for static, forced oscillation and free to oscillate dynamic stability testing in a wind tunnel without the need for a physical support. The objectives of study are to assist in the application of the free to oscillate testing method in an MSBS to determine dynamic stability characteristics for various re-entry capsule designs.

This thesis discusses the development and testing of a launching method called the grabber for use in the MSBS Subsonic Wind Tunnel at NASA Langley Research Center. Aerodynamic tests were run to support the use of this method and compare the …

Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan, Clark N. Taylor, Scott L. Nykl

Faculty Publications

One of the fundamental problems of robotics and navigation is the estimation of the relative pose of an external object with respect to the observer. A common method for computing the relative pose is the iterative closest point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in downstream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this paper, a novel method for estimating uncertainty from sensed data is …

Crazyflie 2.1 Quadcopter Nonlinear System Identification, Nhat V. Nguyen, Hope Storro, John Plimpton

2023 Symposium

Quadcopters (quad) are used widely in many industries with crucial applications such as infrastructure inspection or package delivery. The Crazyflie 2.1 quad from Bitcraze provides an excellent platform for research and development. In this project, our goal is to perform system identification on the Crazyflie to propose a complete model. A gray box method is explored, which includes leveraging the parameters that are already known, to develop a set of equations. Through theory, simulations, and measurements, a complete quadcopter model is developed.

Instrumented Control Column For Optionally Piloted Aircraft, Andrew J. Klein

Electrical Engineering

Natilus, an aerospace company that is rapid-prototyping optionally piloted aircraft (OPA) for the shipping industry, needs a system that retrieves control column position data in order to manipulate flight simulator parameters in software. At present, a universally compatible system for all aircraft does not exist. Typically, established aerospace companies will sink significant time and money into developing proprietary systems for control column data retrieval as every aircraft is unique in its layout and linkage design. However, as a startup developing their first aircraft, Natilus does not have the privilege of modifying an existing sensor system to work with their HIL …

Gyroless Nanosatellite Attitude Determination Using An Array Of Spatially Distributed Accelerometers, Kory J. Haydon

Master's Theses

The low size and budget of typical nanosatellite missions limit the available sensors for attitude estimation. Relatively high noise MEMS gyroscopes often must be employed when accurate knowledge of the spacecraft’s angular velocity is necessary for attitude determination and control. This thesis derived and tested in simulation the “Virtual Gyroscope” algorithm, which replaced a standard gyroscope with an array of spatially distributed accelerometers for a 1U CubeSat mission. A MEMS accelerometer model was developed and validated using Root Allan Variance, and the Virtual Gyroscope was tested both in the open loop configuration and as a replacement for a gyroscope in …

Distributed Control Of Servicing Satellite Fleet Using Horizon Simulation Framework, Scott Plantenga

Master's Theses

On-orbit satellite servicing is critical to maximizing space utilization and sustainability and is of growing interest for commercial, civil, and defense applications. Reliance on astronauts or anchored robotic arms for the servicing of next-generation large, complex space structures operating beyond Low Earth Orbit is impractical. Substantial literature has investigated the mission design and analysis of robotic servicing missions that utilize a single servicing satellite to approach and service a single target satellite. This motivates the present research to investigate a fleet of servicing satellites performing several operations for a large, central space structure.

This research leverages a distributed control approach, …

An Online Adaptive Machine Learning Framework For Autonomous Fault Detection, Nolan Coulter

Doctoral Dissertations and Master's Theses

The increasing complexity and autonomy of modern systems, particularly in the aerospace industry, demand robust and adaptive fault detection and health management solutions. The development of a data-driven fault detection system that can adapt to varying conditions and system changes is critical to the performance, safety, and reliability of these systems. This dissertation presents a novel fault detection approach based on the integration of the artificial immune system (AIS) paradigm and Online Support Vector Machines (OSVM). Together, these algorithms create the Artificial Immune System augemented Online Support Vector Machine (AISOSVM).

The AISOSVM framework combines the strengths of the AIS and …

Online Estimation Of Unknown Parameters For Flexible Spacecraft, Nicolo Woodward

Doctoral Dissertations and Master's Theses

Attitude controls methods of highly flexible spacecraft have seen increased interest over the last decades thanks to the technological development of flexible solar panels and deploy-ables, which improves the capabilities of small satellites. However, a high-fidelity model of the flexible mode dynamics is hard to obtain in on-ground testing because not all modes of frequencies can be observed, complicating the controller design. Furthermore, plastic deformations due to long periods of storage of stowed flexible components could result in exciting frequencies outside of the designed controller’s bandwidth, leading to an uncontrollable system. This thesis proposes a method to develop a high-fidelity …