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Articles 1 - 30 of 109
Full-Text Articles in Navigation, Guidance, Control and Dynamics
Identification Of Authentic Gnss Signals In Time-Differenced Carrier-Phase Measurements With A Software-Defined Radio Receiver, Zhen Zhu, Sanjeev Gunawardena, Eric Vinande, Jason Pontious
Identification Of Authentic Gnss Signals In Time-Differenced Carrier-Phase Measurements With A Software-Defined Radio Receiver, Zhen Zhu, Sanjeev Gunawardena, Eric Vinande, Jason Pontious
Faculty Publications
The time-differenced carrier phase can be computed from measurements recorded by a multi-global navigation satellite system software-defined radio receiver such as PyChips, from which the user displacement and receiver clock drift can be solved. PyChips is able to simultaneously track authentic and inauthentic signals in separate channels, which makes it possible to observe both types of measurements with corresponding navigation data. A random sample consensus algorithm has been introduced to assess the consistency between the measurements and data. This algorithm successfully separated authentic channels from inauthentic channels when they are broadcast simultaneously.
Machine Visual Perception From Sim-To-Real Transfer Learning For Autonomous Docking Maneuvers, Derek Worth, Jeffrey Choate, Ryan M. Raettig, Scott L. Nykl, Clark N. Taylor
Machine Visual Perception From Sim-To-Real Transfer Learning For Autonomous Docking Maneuvers, Derek Worth, Jeffrey Choate, Ryan M. Raettig, Scott L. Nykl, Clark N. Taylor
Faculty Publications
This paper presents a comprehensive approach to enhancing autonomous docking maneuvers through machine visual perception and sim-to-real transfer learning. By leveraging relative vectoring techniques, we aim to replicate the human ability to execute precise docking operations. Our study focuses on autonomous aerial refueling as a use case, demonstrating significant advancements in relative navigation and object detection. We introduce a novel method for aligning digital twins using fiducial targets and motion capture data, which facilitates accurate pose estimation from real-world imagery. Additionally, we develop cost-efficient annotation automation techniques for generating high-quality You Only Look Once training data. Experimental results indicate that …
Magnetic Sensor Compensation Utilizing Factor Graph Estimation, Frederic W. Lathrop, Clark N. Taylor, Aaron Nielsen
Magnetic Sensor Compensation Utilizing Factor Graph Estimation, Frederic W. Lathrop, Clark N. Taylor, Aaron Nielsen
Faculty Publications
Recently, there has been significant interest in the ability to navigate without GPS using the magnetic anomaly field of the Earth (magnav). One of the key technical bottlenecks to achieving magnav is obtaining an accurate magnetic sensor calibration, taking into account own-ship and sensor effects. The Tolles-Lawson magnetic calibration method continues to be the industry standard and was developed when airborne magnetic survey aircraft were first employed over 70 years ago. In this paper, we present a magnetic calibration algorithm based on a factor graph optimization using inertial measurements as well as inputs from both a vector and scalar magnetometer. …
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 …
Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation, Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen, Ying-Cheng Lai, Aaron P. Nielsen
Random Forests For Detecting Weak Signals And Extracting Physical Information: A Case Study Of Magnetic Navigation, Mohammadamin Moradi, Zheng-Meng Zhai, Aaron Nielsen, Ying-Cheng Lai, Aaron P. Nielsen
Faculty Publications
It has been recently demonstrated that two machine-learning architectures, reservoir computing and time-delayed feed-forward neural networks, can be exploited for detecting the Earth’s anomaly magnetic field immersed in overwhelming complex signals for magnetic navigation in a GPS-denied environment. The accuracy of the detected anomaly field corresponds to a positioning accuracy in the range of 10–40 m. To increase the accuracy and reduce the uncertainty of weak signal detection as well as to directly obtain the position information, we exploit the machine-learning model of random forests that combines the output of multiple decision trees to give optimal values of the physical …
Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won
Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won
Faculty Publications
Taking the work conducted by the global navigation satellite system (GNSS) software-defined radio (SDR) working group during the last decade as a seed, this contribution summarizes, for the first time, the history of GNSS SDR development. This report highlights selected SDR implementations and achievements that are available to the public or that influenced the general development of SDR. Aspects related to the standardization process of intermediate-frequency sample data and metadata are discussed, and an update of the Institute of Navigation SDR Standard is proposed. This work focuses on GNSS SDR implementations in general-purpose processors and leaves aside developments conducted on …
Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan, Clark N. Taylor, Scott L. Nykl
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 …
Resilience Monitoring For Multi-Filter All-Source Navigation Framework With Assurance, Jonathon S. Gipson, Robert C. Leishman
Resilience Monitoring For Multi-Filter All-Source Navigation Framework With Assurance, 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 …
Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor
Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor
Faculty Publications
This paper presents a method to estimate the covariances of the inputs in a factor-graph formulation for localization under non-line-of-sight conditions. A general solution based on covariance estimation and M-estimators in linear regression problems, is presented that is shown to give unbiased estimators of multiple variances and are robust against outliers. An iteratively re-weighted least squares algorithm is proposed to jointly compute the proposed variance estimators and the state estimates for the nonlinear factor graph optimization. The efficacy of the method is illustrated in a simulation study using a robot localization problem under various process and measurement models and measurement …
Ion Gnss Software-Defined Radio Metadata Standard, Sanjeev Gunawardena, Thomas Pany, James Curran
Ion Gnss Software-Defined Radio Metadata Standard, Sanjeev Gunawardena, Thomas Pany, James Curran
Faculty Publications
The past several years have seen a proliferation of software‐defined radio (SDR) data collection systems and processing platforms designed for or applicable to satellite navigation (satnav) applications. These systems necessarily produce datasets in a wide range of different formats. To correctly interpret this SDR data, essential information such as the packed sample format and sampling rate is needed. Communicating this metadata between creators and users has historically been an ad‐hoc, cumbersome, and error‐prone process. To address this issue, the satnav SDR community developed a metadata standard and normative software library to automate this process, thus simplifying the exchange of datasets …
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 …
An Analysis Of The Benefits And Difficulties Of Aerial Magnetic Vector Navigation, Aaron J. Canciani, Christopher J. Brennan
An Analysis Of The Benefits And Difficulties Of Aerial Magnetic Vector Navigation, Aaron J. Canciani, Christopher J. Brennan
Faculty Publications
Recent successful flight tests have demonstrated scalar magnetic anomaly navigation to be a viable GPS-alternative navigation system. These flight tests matched magnetic field measurements to maps of the Earth's crustal magnetic field in order to navigate. Scalar magnetic navigation uses only the magnetic field intensity, not direction, in order to navigate. While it appears obvious to extend aerial magnetic navigation to use the full vector field, in practice there are substantial obstacles to doing so. This article explores the key challenges of magnetic vector navigation including current sensor limitations, lack of high frequency magnetic vector maps of the Earth's crust, …
Residual-Based Multi-Filter Methodology For All-Source Fault Detection, Exclusion, And Performance Monitoring, Juan Jurado, John F. Raquet, Christine M. Schubert Kabban Air Force Institute Of Technology, Jonathon S. Gipson
Residual-Based Multi-Filter Methodology For All-Source Fault Detection, Exclusion, And Performance Monitoring, Juan Jurado, John F. Raquet, Christine M. Schubert Kabban Air Force Institute Of Technology, Jonathon S. Gipson
Faculty Publications
All-source navigation has become increasingly relevant over the past decade with the development of viable alternative sensor technologies. However, as the number and type of sensors informing a system increases, so does the probability of corrupting the system with sensor modeling errors, signal interference, and undetected faults. Though the latter of these has been extensively researched, the majority of existing approaches have constrained faults to biases and designed algorithms centered around the assumption of simultaneously redundant, synchronous sensors with valid measurement models, none of which are guaranteed for all-source systems. As part of an overall all-source assured or resilient navigation …
Relational Database Design And Multi-Objective Database Queries For Position Navigation And Timing Data, Sean A. Mochocki
Relational Database Design And Multi-Objective Database Queries For Position Navigation And Timing Data, Sean A. Mochocki
Theses and Dissertations
Performing flight tests is a natural part of researching cutting edge sensors and filters for sensor integration. Unfortunately, tests are expensive, and typically take many months of planning. A sensible goal would be to make previously collected data readily available to researchers for future development. The Air Force Institute of Technology (AFIT) has hundreds of data logs potentially available to aid in facilitating further research in the area of navigation. A database would provide a common location where older and newer data sets are available. Such a database must be able to store the sensor data, metadata about the sensors, …
Flight Characteristic Verification Of The Variable Camber Compliant Wing, Sharee B. Acosta
Flight Characteristic Verification Of The Variable Camber Compliant Wing, Sharee B. Acosta
Theses and Dissertations
Morphing wing technology gives aircraft the ability to change wing shape to control the aircraft and flight performance characteristics. AFIT, AFRL and USU Aero Lab have collaborated to design and test a variable camber compliant wing (VCCW) on a small unmanned aerial vehicle (UAV). Flight tests demonstrated the wing performance and provided data to refine a VCCW flight simulator. Work was completed with the USU AeroLab-generated MachUp and the actual flight data to improve the simulator to provide results close to those of the actual flight test. The research provides a tool to reduce time and cost for future flight …
Signal Quality Monitoring Of Gnss Signals Using A Chip Shape Deformation Metric, Nicholas C. Echeverry
Signal Quality Monitoring Of Gnss Signals Using A Chip Shape Deformation Metric, Nicholas C. Echeverry
Theses and Dissertations
The Global Navigation Satellite System continues to become deeply em-bedded within modern civilization, and is depended on for confident, accurate navigation information. High precision position and timing accuracy is typically achieved using differential processing, however these systems provide limited compensation for distortions caused by multi-path or faulty satellite hardware. Signal Quality Monitoring (SQM) aims to provide confidence in a receivers Position, Navigation, and Timing solution and to offer timely warnings in the event that signal conditions degrade to unsafe levels. The methods presented in this document focus on implementing effective SQM using low-cost Commercial Off-the-Shelf equipment, a Software Defined Radio, …
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 …
Magslam: Aerial Simultaneous Localization And Mapping Using Earth's Magnetic Anomaly Field, Taylor N. Lee, Aaron J. Canciani
Magslam: Aerial Simultaneous Localization And Mapping Using Earth's Magnetic Anomaly Field, Taylor N. Lee, Aaron J. Canciani
Faculty Publications
Instances of spoofing and jamming of global navigation satellite systems (GNSSs) have emphasized the need for alternative navigation methods. Aerial navigation by magnetic map matching has been demonstrated as a viable GNSS‐alternative navigation technique. Flight test demonstrations have achieved accuracies of tens of meters over hour‐long flights, but these flights required accurate magnetic maps which are not always available. Magnetic map availability and resolution vary widely around the globe. Removing the dependency on prior survey maps extends the benefits of aerial magnetic navigation methods to small unmanned aerial systems (sUAS) at lower altitudes where magnetic maps are especially undersampled or …
Semantic Segmentation Of Aerial Imagery Using U-Nets, Terence J. Yi
Semantic Segmentation Of Aerial Imagery Using U-Nets, Terence J. Yi
Theses and Dissertations
In situations where global positioning systems are unavailable, alternative methods of localization must be implemented. A potential step to achieving this is semantic segmentation, or the ability for a model to output class labels by pixel. This research aims to utilize datasets of varying spatial resolutions and locations to train a fully convolutional neural network architecture called the U-Net to perform segmentations of aerial images. Variations of the U-Net architecture are implemented and compared to other existing models in order to determine the best in detecting buildings and roads. A final dataset will also be created combining two datasets to …
Verifying And Improving A Flight Reference System's Performance, Loren E. Myers
Verifying And Improving A Flight Reference System's Performance, Loren E. Myers
Theses and Dissertations
The 746th Test Squadron (746 TS) at Holloman AFB, NM operates the Ultra High Accuracy Reference System (UHARS) as part of its mission positioning and navigation test. This research presents a method for verifying the performance of a flight reference system using a Delta-Position velocity derived from radio navigation positioning measurements. The algorithm presented may utilize Global Positioning System (GPS) or the Locata ground based positioning system. In the latter case, Locata provides a velocity truth independent from GPS. The accuracy of Locata and GPS are assessed and UHARS velocity measurements are characterized both in nominal and GPS denied applications.
Improved Ground-Based Monocular Visual Odometry Estimation Using Inertially-Aided Convolutional Neural Networks, Josiah D. Watson
Improved Ground-Based Monocular Visual Odometry Estimation Using Inertially-Aided Convolutional Neural Networks, Josiah D. Watson
Theses and Dissertations
While Convolutional Neural Networks (CNNs) can estimate frame-to-frame (F2F) motion even with monocular images, additional inputs can improve Visual Odometry (VO) predictions. In this thesis, a FlowNetS-based [1] CNN architecture estimates VO using sequential images from the KITTI Odometry dataset [2]. For each of three output types (full six degrees of freedom (6-DoF), Cartesian translation, and transitional scale), a baseline network with only image pair input is compared with a nearly identical architecture that is also given an additional rotation estimate such as from an Inertial Navigation System (INS). The inertially-aided networks show an order of magnitude improvement over the …
Ion Software-Defined Radio Metadata Standard Final Report, Sanjeev Gunawardena, Alexander Rugamer, Muhammad Subhan Hameed, Markel Arizabaleta, Thomas Pany, Javier Arribas
Ion Software-Defined Radio Metadata Standard Final Report, Sanjeev Gunawardena, Alexander Rugamer, Muhammad Subhan Hameed, Markel Arizabaleta, Thomas Pany, Javier Arribas
Faculty Publications
The ION GNSS SDR Metadata Standard describes the formatting and other essential PNT-related parameters of sampled data streams and files. This allows processors to seamlessly consume such data without the need to input these parameters manually. The technical development phase of the initial version of the standard has now been deemed complete and is currently undergoing the last remaining procedural steps towards adoption as a formal standard by the Institute of Navigation. This paper reports on the activities of the working group since September 2018 and summarizes the final products of the standard. It also reports on examples of early …
First Approach To Coupling Of Numerical Lifting-Line Theory And Linear Covariance Analysis For Uav State Uncertainty Propagation, Cory D. Goates, Randall S. Christensen, Robert C. Leishman
First Approach To Coupling Of Numerical Lifting-Line Theory And Linear Covariance Analysis For Uav State Uncertainty Propagation, Cory D. Goates, Randall S. Christensen, Robert C. Leishman
Faculty Publications
Numerical lifting-line is a computationally efficient method for calculating aerodynamic forces and moments on aircraft. However, its potential has yet to be tapped for use in guidance, navigation, and control (GN&C). Linear covariance analysis is becoming a popular GN&C design tool and shows promise for pairing with numerical lifting-line. Pairing numerical lifting-line with linear covariance analysis allows for forward propagation of state uncertainty for real-time decision making. We demonstrate this for select state variables in a drone aerial recapture situation. Linear covariance analysis uses finite difference derivatives obtained from numerical lifting-line to calculate force and moment variances. These show agreement …
Magnetic Field Aided Indoor Navigation, William F. Storms
Magnetic Field Aided Indoor Navigation, William F. Storms
Theses and Dissertations
This research effort examines inertial navigation system aiding using magnetic field intensity data and a Kalman filter in an indoor environment. Many current aiding methods do not work well in an indoor environment, like aiding using the Global Positioning System. The method presented in this research uses magnetic field intensity data from a three-axis magnetometer in order to estimate position using a maximum – likelihood approach. The position measurements are then combined with a motion model using a Kalman filter. The magnetic field navigation algorithm is tested using a combination of simulated and real measurements. These tests are conducted using …
Real-Time Path Planning In Constrained, Uncertain Environments, Randall Christensen, Robert C. Leishman
Real-Time Path Planning In Constrained, Uncertain Environments, Randall Christensen, Robert C. Leishman
Faculty Publications
A key enabler of autonomous vehicles is the ability to plan the path of the vehicle to accomplish mission objectives. To be robust to realistic environments, path planners must account for uncertainty in the trajectory of the vehicle as well as uncertainty in the location of obstacles. The uncertainty in the trajectory of the vehicle is a difficult quantity to estimate, and is influenced by coupling between the vehicle dynamics, guidance, navigation, and control system as well as any disturbances acting on the vehicle. Monte Carlo analysis is the conventional approach to determine vehicle dispersion, while accounting for the coupled …
Navigation With Artificial Neural Networks, Joseph A. Curro Ii
Navigation With Artificial Neural Networks, Joseph A. Curro Ii
Theses and Dissertations
The objective of this dissertation is to explore the applications for Artificial Neural Networks (ANNs) in the field of Navigation. The state of the art for ANNs has improved significantly so now they can rival and even surpass humans in problems once thought impossible. We present different methods to augment, combine, or replace existing Navigation filters with ANN. The main focus of these methods is to use as much existing knowledge as possible then use ANNs to extend the current knowledge base. Next, improvements are made for a class of Artificial Neural Network (ANN)s which provide covariance called Mixture Density …
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 …
Optimal Control Methods For Missile Evasion, Ryan W. Carr
Optimal Control Methods For Missile Evasion, Ryan W. Carr
Theses and Dissertations
Optimal control theory is applied to the study of missile evasion, particularly in the case of a single pursuing missile versus a single evading aircraft. It is proposed to divide the evasion problem into two phases, where the primary considerations are energy and maneuverability, respectively. Traditional evasion tactics are well documented for use in the maneuverability phase. To represent the first phase dominated by energy management, the optimal control problem may be posed in two ways, as a fixed final time problem with the objective of maximizing the final distance between the evader and pursuer, and as a free final …
Small Fixed-Wing Aerial Positioning Using Inter-Vehicle Ranging Combined With Visual Odometry, Benjamin M. Fain
Small Fixed-Wing Aerial Positioning Using Inter-Vehicle Ranging Combined With Visual Odometry, Benjamin M. Fain
Theses and Dissertations
There has been increasing interest in developing the ability for small unmanned aerial systems (SUAS) to be able to operate in environments where GPS is not available. This research considers the case of a larger aircraft loitering above a smaller GPS-denied SUAS. This larger aircraft is assumed to have greater resources which can overcome the GPS jamming and provide range information to the SUAS flying a mission below. This research demonstrates that using a ranging update combined with an aircraft motion model and visual odometry can greatly improve the accuracy of a SUASs estimated position in a GPS-denied environment.
Combined Stereo Vision And Inertial Navigation For Automated Aerial Refueling, Daniel T. Johnson
Combined Stereo Vision And Inertial Navigation For Automated Aerial Refueling, Daniel T. Johnson
Theses and Dissertations
This paper describes the design of an EKF to obtain the precise relative position of two aircraft in a refueling maneuver while operating in GPS denied environments. The EKF uses the INS already present in both aircraft as well as the stereo camera system organic to new tanker systems. The aircraft trajectories are generated according to authentic refueling profiles with flight dynamics software and executed in a 3D virtual environment to enable deterministic simulation of the stereo camera system and to demonstrate the effectiveness of the combined system in a refueling scenario. Results show the system can achieve sufficient accuracy …