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Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor
Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor
Faculty Publications
Once realized, autonomous aerial refueling will revolutionize unmanned aviation by removing current range and endurance limitations. Previous attempts at establishing vision-based solutions have come close but rely heavily on near perfect extrinsic camera calibrations that often change midflight. In this paper, we propose dual object detection, a technique that overcomes such requirement by transforming aerial refueling imagery directly into receiver aircraft reference frame probe-to-drogue vectors regardless of camera position and orientation. These vectors are precisely what autonomous agents need to successfully maneuver the tanker and receiver aircraft in synchronous flight during refueling operations. Our method follows a common 4-stage process …
Using Embedded Systems And Augmented Reality For Automated Aerial Refueling, Nathaniel A. Wilson
Using Embedded Systems And Augmented Reality For Automated Aerial Refueling, Nathaniel A. Wilson
Theses and Dissertations
The goal of automated aerial refueling (AAR) is to extend the range of unmanned aircraft. Control latency prevents a human from remotely controlling the receiving aircraft as it approaches a tanker. To conform with the size, weight, and power constraints of a small unmanned aircraft, an AAR system must execute in real-time on an embedded platform. This thesis explores the timing and computational performance of a NVIDIA Jetson AGX Orin to a state-of-the-art general-purpose computer using existing AAR algorithms. It also constructs an augmented reality framework as an intermediate step for testing vision-based AAR algorithms between virtual testing and expensive …
Using Generative Adversarial Networks To Augment Unmanned Aerial Vehicle Image Classification Training Sets, Benjamin J. Mccloskey
Using Generative Adversarial Networks To Augment Unmanned Aerial Vehicle Image Classification Training Sets, Benjamin J. Mccloskey
Theses and Dissertations
A challenging task in computer vision is finding techniques to improve the object detection and classification capabilities of ML models used for processing images acquired by moving aerial platforms. This research explores if GAN augmented UAV training sets can increase the generalizability of a detection model trained on said data. To answer this question, the YOLOv4-Tiny Object Detection Model was trained with aerial image training sets depicting rural environments. The salient objects within the frames were recreated using various GAN architectures, placed back into the original frames, and the augmented frames appended to the original training sets. GAN augmentation on …
Real Time Evaluation Of Boom And Drogue Occlusion With Aar, Xiaoyang Wu
Real Time Evaluation Of Boom And Drogue Occlusion With Aar, Xiaoyang Wu
Theses and Dissertations
In recent years, Unmanned Aerial Vehicles (UAV) have seen a rise in popularity. Various navigational algorithms have been developed as a solution to estimate a UAV’s pose relative to the refueler aircraft. The result can be used to safely automate aerial refueling (AAR) to improve UAVs’ time-on-station and ensure the success of military operations. This research aims to reach real-time performance using a GPU accelerated approach. It also conducts various experiments to quantify the effects of refueling boom/drogue occlusion and image exposure on the pose estimation pipeline in a lab setting.
Monocular Pose Estimation For Automated Aerial Refueling Via Perspective-N-Point, James C. Lynch
Monocular Pose Estimation For Automated Aerial Refueling Via Perspective-N-Point, James C. Lynch
Theses and Dissertations
Any Automated Aerial Refueling (AAR) solution requires the quick and precise estimation of the relative position and rotation of the two aircraft involved. This is currently accomplished using stereo vision techniques augmented by Iterative Closest Point (ICP), but requires post-processing to account for environmental factors such as boom occlusion. This paper proposes a monocular solution, combining a custom-trained single-shot object detection Convolutional Neural Network (CNN) and Perspective-n-Point (PnP) estimation to calculate a pose estimate with a single image. This solution is capable of pose estimation at contact point (22m) within 7cm of error and a rate of 10Hz, regardless of …
Smoothing Of Convolutional Neural Network Classifications, Glen R. Drumm
Smoothing Of Convolutional Neural Network Classifications, Glen R. Drumm
Theses and Dissertations
Smoothing convolutional neural networks is investigated. When intermittent and random false predictions happen, a technique of average smoothing is applied to smooth out the incorrect predictions. While a simple problem environment shows proof of concept, obstacles remain for applying such a technique to a more operationally complex problem.
Stereo Camera Calibrations With Optical Flow, Joshua D. Larson
Stereo Camera Calibrations With Optical Flow, Joshua D. Larson
Theses and Dissertations
Remotely Piloted Aircraft (RPA) are currently unable to refuel mid-air due to the large communication delays between their operators and the aircraft. AAR seeks to address this problem by reducing the communication delay to a fast line-of-sight signal between the tanker and the RPA. Current proposals for AAR utilize stereo cameras to estimate where the receiving aircraft is relative to the tanker, but require accurate calibrations for accurate location estimates of the receiver. This paper improves the accuracy of this calibration by improving three components of it: increasing the quantity of intrinsic calibration data with CNN preprocessing, improving the quality …
Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan
Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan
Theses and Dissertations
One of the fundamental problems of robotics and navigation is the estimation of 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 down-stream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this thesis a novel method for estimating uncertainty from sensed data is introduced. …
A Comparative Evaluation Of The Fast Optical Pulse Response Of Event-Based Cameras, Tyler J. Brewer
A Comparative Evaluation Of The Fast Optical Pulse Response Of Event-Based Cameras, Tyler J. Brewer
Theses and Dissertations
Event cameras use biologically inspired readout circuit architecture to offer a faster and more efficient method of imaging than traditional frame-based detectors. The asynchronous event reporting circuit timestamps events to 1 microsecond resolution, but latency increases when many pixels are stimulated simultaneously. To characterize this variability, the DAVIS240, DAVIS346, DVXPlorer, and Prophesee Gen3M VGA-CD 1.1 cameras were exposed to single step-function flashes with amplitudes from 9.3-771cd/m2, stimulating from 0.0042-100 of pixels. The Median Absolute Deviation of pixel response times ranged between 0 and 6086µs, increasing with the percent of pixels stimulated (PSP). The number of events generated per …
Object Detection With Deep Learning To Accelerate Pose Estimation For Automated Aerial Refueling, Andrew T. Lee
Object Detection With Deep Learning To Accelerate Pose Estimation For Automated Aerial Refueling, Andrew T. Lee
Theses and Dissertations
Remotely piloted aircraft (RPAs) cannot currently refuel during flight because the latency between the pilot and the aircraft is too great to safely perform aerial refueling maneuvers. However, an AAR system removes this limitation by allowing the tanker to directly control the RP A. The tanker quickly finding the relative position and orientation (pose) of the approaching aircraft is the first step to create an AAR system. Previous work at AFIT demonstrates that stereo camera systems provide robust pose estimation capability. This thesis first extends that work by examining the effects of the cameras' resolution on the quality of pose …
Maximizing Accuracy Through Stereo Vision Camera Positioning For Automated Aerial Refueling, Kirill A. Sarantsev
Maximizing Accuracy Through Stereo Vision Camera Positioning For Automated Aerial Refueling, Kirill A. Sarantsev
Theses and Dissertations
Aerial refueling is a key component of the U.S. Air Force strategic arsenal. When two aircraft interact in an aerial refueling operation, the accuracy of relative navigation estimates are critical for the safety, accuracy and success of the mission. Automated Aerial Refueling (AAR) looks to improve the refueling process by creating a more effective system and allowing for Unmanned Aerial Vehicle(s) (UAV) support. This paper considers a cooperative aerial refueling scenario where stereo cameras are used on the tanker to direct a \boom" (a large, long structure through which the fuel will ow) into a port on the receiver aircraft. …
Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl
Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl
Theses and Dissertations
The United States Air Force (USAF) executes five Core Missions, four of which depend on increased aircraft range. To better achieve global strike and reconnaissance, unmanned aerial vehicles (UAVs) require aerial refueling for extended missions. However, current aerial refueling capabilities are limited to manned aircraft due to technical difficulties to refuel UAVs mid-flight. The latency between a UAV operator and the UAV is too large to adequately respond for such an operation. To overcome this limitation, the USAF wants to create a capability to guide the refueling boom into the refueling receptacle. This research explores the use of light detection …
Infrared And Electro-Optical Stereo Vision For Automated Aerial Refueling, William E. Dallmann
Infrared And Electro-Optical Stereo Vision For Automated Aerial Refueling, William E. Dallmann
Theses and Dissertations
Currently, Unmanned Aerial Vehicles are unsafe to refuel in-flight due to the communication latency between the UAVs ground operator and the UAV. Providing UAVs with an in-flight refueling capability would improve their functionality by extending their flight duration and increasing their flight payload. Our solution to this problem is Automated Aerial Refueling (AAR) using stereo vision from stereo electro-optical and infrared cameras on a refueling tanker. To simulate a refueling scenario, we use ground vehicles to simulate a pseudo tanker and pseudo receiver UAV. Imagery of the receiver is collected by the cameras on the tanker and processed by a …
Integrity Monitoring For Automated Aerial Refueling: A Stereo Vision Approach, Thomas R. Stuart
Integrity Monitoring For Automated Aerial Refueling: A Stereo Vision Approach, Thomas R. Stuart
Theses and Dissertations
Unmanned aerial vehicles (UAVs) increasingly require the capability to y autonomously in close formation including to facilitate automated aerial refueling (AAR). The availability of relative navigation measurements and navigation integrity are essential to autonomous relative navigation. Due to the potential non-availability of the global positioning system (GPS) during military operations, it is highly desirable that relative navigation can be accomplished without the use of GPS. This paper develops two algorithms designed to provide relative navigation measurements solely from a stereo image pair. These algorithms were developed and analyzed in the context of AAR using a stereo camera system modeling that …
Position And Volume Estimation Of Atmospheric Nuclear Detonations From Video Reconstruction, Daniel T. Schmitt
Position And Volume Estimation Of Atmospheric Nuclear Detonations From Video Reconstruction, Daniel T. Schmitt
Theses and Dissertations
Recent work in digitizing films of foundational atmospheric nuclear detonations from the 1950s provides an opportunity to perform deeper analysis on these historical tests. This work leverages multi-view geometry and computer vision techniques to provide an automated means to perform three-dimensional analysis of the blasts for several points in time. The accomplishment of this requires careful alignment of the films in time, detection of features in the images, matching of features, and multi-view reconstruction. Sub-explosion features can be detected with a 67% hit rate and 22% false alarm rate. Hotspot features can be detected with a 71.95% hit rate, 86.03% …
Covariance Analysis Of Vision Aided Navigation By Bootstrapping, Andrew L. Relyea
Covariance Analysis Of Vision Aided Navigation By Bootstrapping, Andrew L. Relyea
Theses and Dissertations
Inertial Navigation System (INS) aiding using bearing measurements taken over time of stationary ground features is investigated. A cross country flight, in two and three dimensional space, is considered, as well as a vertical drop in three dimensional space. The objective is to quantify the temporal development of the uncertainty in the navigation states of an aircraft INS which is aided by taking bearing measurements of ground objects which have been geolocated using ownship position. It is shown that during wings level flight at constant speed and a fixed altitude, an aircraft that tracks ground objects and over time sequentially …
Using Predictive Rendering As A Vision-Aided Technique For Autonomous Aerial Refueling, Adam D. Weaver
Using Predictive Rendering As A Vision-Aided Technique For Autonomous Aerial Refueling, Adam D. Weaver
Theses and Dissertations
This research effort seeks to characterize a vision-aided approach for an Unmanned Aerial System (UAS) to autonomously determine relative position to another aircraft in a formation, specifically to address the autonomous aerial refueling problem. A system consisting of a monocular digital camera coupled with inertial sensors onboard the UAS is analyzed for feasibility of using this vision-aided approach. A three-dimensional rendering of the tanker aircraft is used to generate predicted images of the tanker as seen by the receiver aircraft. A rigorous error model is developed to model the relative dynamics between an INS-equipped receiver and the tanker aircraft. A …
Collision Avoidance For Uavs Using Optic Flow Measurement With Line Of Sight Rate Equalization And Looming, Paul J. Shelnutt
Collision Avoidance For Uavs Using Optic Flow Measurement With Line Of Sight Rate Equalization And Looming, Paul J. Shelnutt
Theses and Dissertations
A series of simplified scenarios is investigated whereby an optical flow balancing guidance law is used to avoid obstacles by steering an air vehicle between fixed objects/obstacles. These obstacles are registered as specific points that can be representative of features in a scene. The obstacles appear in the field of view of a single forward looking camera. First a 2-D analysis is presented where the rate of the line of sight from the vehicle to each of the obstacles to be avoided is measured. The analysis proceeds by initially using no field of view (FOV) limitations, then applying FOV restrictions, …
Determination Of Structure From Motion Using Aerial Imagery, Paul R. Graham
Determination Of Structure From Motion Using Aerial Imagery, Paul R. Graham
Theses and Dissertations
The structure from motion process creates three-dimensional models from a sequence of images. Until recently, most research in this field has been restricted to land-based imagery. This research examines the current methods of land-based structure from motion and evaluates their performance for aerial imagery. Current structure from motion algorithms search the initial image for features to track though the subsequent images. These features are used to create point correspondences between the two images. The correspondences are used to estimate the motion of the camera and then the three-dimensional structure of the scene. This research tests current algorithms using synthetic data …