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Navigation, Guidance, Control, and Dynamics Commons™
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Articles 1 - 7 of 7
Full-Text Articles in Navigation, Guidance, Control, and Dynamics
Hyperparameter Tuning For Robust Autonomous Vehicle Vision, Nico D. De Ros
Hyperparameter Tuning For Robust Autonomous Vehicle Vision, Nico D. De Ros
Theses and Dissertations
Classification “flickering,” where the classification of an object changes inconsistently between consecutive video frames, remains a persistent issue in modern object classification algorithms. This problem undermines the reliability of autonomous vision systems and poses significant risks in high-stakes applications such as autonomous vehicles. This thesis explores the use of response surface methodology, a statistical design of experiments technique, to optimize hyperparameters across three object classification pipelines. The first pipeline combines YOLOv8 with SORT to establish a benchmark. The second integrates a Bayesian back-end, while the third employs an exponential smoothing back-end. Hyperparameter tuning was conducted using a two-step process: an …
Decision Support Issues In Automated Driving Systems, William N. Caballero, David Ríos Insua, David Banks
Decision Support Issues In Automated Driving Systems, William N. Caballero, David Ríos Insua, David Banks
Faculty Publications
Machine learning and computational processing have advanced such that automated driving systems (ADSs) are no longer a distant reality. Many automobile manufacturers have developed prototypes; however, there exist numerous decision support issues requiring resolution to ensure mass ADS adoption. In the coming decades, it is likely that production ADSs will only be partially autonomous. Such ADSs operate within predetermined conditions and require driver intervention when they are violated. Since forecasts of their 20-year market penetration are relatively low, ADSs will likely operate in heterogeneous traffic characterized by vehicles of varying autonomy levels. Under these conditions, effective decision support must consider …
Ground Vehicle Navigation With Depth Camera And Tracking Camera, Hongseok Kim
Ground Vehicle Navigation With Depth Camera And Tracking Camera, Hongseok Kim
Theses and Dissertations
The aim of this research is to provide autonomous navigation of a 4 wheel vehicle using commercial, off-the-shelf depth and tracking cameras. Some sensitive operations need accuracy within a few inches of navigation ability for indoor or outdoor scenarios where GPS signals are not available. Combination of the Visual Odometry (VO), Distance-Depth (D-D), and Object Detection data from the cameras can be used for accurate navigation and object avoidance. The Intel RealSense D435i, a depth camera, generates depth measurements and the relative position vector of an object. The Intel RealSense T265, a tracking camera, generates its own coordinate system and …
Resilience For Multi-Filter All-Source Navigation Framework With Integrity, Jonathon S. Gipson, Robert C. Leishman
Resilience For Multi-Filter All-Source Navigation Framework With Integrity, Jonathon S. Gipson, Robert C. Leishman
Faculty Publications
The Autonomous and Resilient Management of All-source Sensors (ARMAS) framework monitors residual-space test statistics across unique sensor-exclusion banks of filters, (known as subfilters) to provide a resilient, fault-resistant all-source navigation architecture with assurance. A critical assumption of this architecture, demonstrated in this paper, is fully overlapping state observability across all subfilters. All-source sensors, particularly those that only provide partial state information (altimeters, TDoA, AOB, etc.) do not intrinsically meet this requirement.
This paper presents a novel method to monitor real-time overlapping position state observability and introduces an "observability bank" within the ARMAS framework, known as Stable Observability Monitoring (SOM). SOM …
Pedestrian Navigation Using Artificial Neural Networks And Classical Filtering Techniques, David J. Ellis
Pedestrian Navigation Using Artificial Neural Networks And Classical Filtering Techniques, David J. Ellis
Theses and Dissertations
The objective of this thesis is to explore the improvements achieved through using classical filtering methods with Artificial Neural Network (ANN) for pedestrian navigation techniques. ANN have been improving dramatically in their ability to approximate various functions. These neural network solutions have been able to surpass many classical navigation techniques. However, research using ANN to solve problems appears to be solely focused on the ability of neural networks alone. The combination of ANN with classical filtering methods has the potential to bring beneficial aspects of both techniques to increase accuracy in many different applications. Pedestrian navigation is used as a …
Assessing The Competing Characteristics Of Privacy And Safety Within Vehicular Ad Hoc Networks, Jacob W. Connors
Assessing The Competing Characteristics Of Privacy And Safety Within Vehicular Ad Hoc Networks, Jacob W. Connors
Theses and Dissertations
The introduction of Vehicle-to-Vehicle (V2V) communication has the promise of decreasing vehicle collisions, congestion, and emissions. However, this technology places safety and privacy at odds; an increase of safety applications will likely result in the decrease of consumer privacy. The National Highway Traffic Safety Administration (NHTSA) has proposed the Security Credential Management System (SCMS) as the back end infrastructure for maintaining, distributing, and revoking vehicle certificates attached to every Basic Safety Message (BSM). This Public Key Infrastructure (PKI) scheme is designed around the philosophy of maintaining user privacy through the separation of functions to prevent any one subcomponent from identifying …
Coded Aperture Aided Navigation And Geolocation Systems, Jamie R. Morrison, John F. Raquet, Michael J. Veth
Coded Aperture Aided Navigation And Geolocation Systems, Jamie R. Morrison, John F. Raquet, Michael J. Veth
AFIT Patents
A micro air vehicle having a navigation system with a single camera to determine position and attitude of the vehicle using changes the direction to the observed features. The difference between the expected directions to the observed features versus the measured direction to the observed features is used to correct a navigation solution.