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Articles 1 - 18 of 18
Full-Text Articles in Aerospace Engineering
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 …
Jointly-Learnt Networks For Future Action Anticipation Via Self-Knowledge Distillation And Cycle Consistency, Md Moniruzzaman, Zhaozheng Yin, Zhihai He, Ming-Chuan Leu, Ruwen Qin
Jointly-Learnt Networks For Future Action Anticipation Via Self-Knowledge Distillation And Cycle Consistency, Md Moniruzzaman, Zhaozheng Yin, Zhihai He, Ming-Chuan Leu, Ruwen Qin
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Future action anticipation aims to infer future actions from the observation of a small set of past video frames. In this paper, we propose a novel Jointly learnt Action Anticipation Network (J-AAN) via Self-Knowledge Distillation (Self-KD) and cycle consistency for future action anticipation. In contrast to the current state-of-the-art methods which anticipate the future actions either directly or recursively, our proposed J-AAN anticipates the future actions jointly in both direct and recursive ways. However, when dealing with future action anticipation, one important challenge to address is the future's uncertainty since multiple action sequences may come from or be followed by …
Nonlinear Intelligent Model Predictive Control Of Mobile Robots, Benjamin Albia
Nonlinear Intelligent Model Predictive Control Of Mobile Robots, Benjamin Albia
Theses and Dissertations
This thesis presents a framework for an artificial neural network (ANN) model-based nonlinear model predictive control of mobile ground robots. A computer vision analysis module was first developed to extract quantitative position information from onboard camera feed with respect to a prescribed path. Various strategies were developed to construct nonlinear physical plant models for model predictive control (MPC), including the physics-based model (PBM), the ANN trained on PBM-generated data, the ANN trained on test-captured data, and the ANN initially trained on PBM-generated data and then retrained with captured data. All the models predict physical states and positions of the robot …
Visual Navigation And Control For Spacecraft Proximity Operations With Unknown Targets, Wyatt J. Harris
Visual Navigation And Control For Spacecraft Proximity Operations With Unknown Targets, Wyatt J. Harris
Theses and Dissertations
Many current and future spacecraft missions must conduct rendezvous and proximity operations (RPO) with resident space objects (RSOs). An important subset of spacecraft RPO that is yet to be demonstrated on-orbit involves final approach maneuvers with respect to RSOs where no information (such as geometry, inertia, relative velocity, etc.) is known about the target a priori, and no information is actively provided by the target during maneuvering. Such operation with respect to ‘unknown’ targets represents an important possible mission set for Department of Defense spacecraft and is the subject of this research. Two visual servoing frameworks capable of autonomously controlling …
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 …
Satellite Articulation Sensing Using Computer Vision, David H. Curtis
Satellite Articulation Sensing Using Computer Vision, David H. Curtis
Theses and Dissertations
Autonomous on-orbit satellite servicing benefits from an inspector satellite that can gain as much information as possible about the primary satellite. This includes performance of articulated objects such as solar arrays, antennas, and sensors. A method for building an articulated model from monocular imagery using tracked feature points and the known relative inspection route is developed. Two methods are also developed for tracking the articulation of a satellite in real-time given an articulated model using both tracked feature points and image silhouettes. Performance is evaluated for multiple inspection routes and the effect of inspection route noise is assessed. Additionally, 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 …
Improving Real-World Performance Of Vision Aided Navigation In A Flight Environment, Donald T. Venable
Improving Real-World Performance Of Vision Aided Navigation In A Flight Environment, Donald T. Venable
Theses and Dissertations
The motivation of this research is to fuse information from an airborne imaging sensor with information extracted from satellite imagery in order to provide accurate position when GPS is unavailable for an extended duration. A corpus of existing geo-referenced satellite imagery is used to create a key point database. A novel algorithm for recovering coarse pose using by comparing key points extracted from the airborne imagery to the reference database is developed. This coarse position is used to bootstrap a local-area geo-registration algorithm, which provides GPS-level position estimates. This research derives optimizations for existing local-area methods for operation in flight …
A Monocular Slam Method To Estimate Relative Pose During Satellite Proximity Operations, Scott J. Kelly
A Monocular Slam Method To Estimate Relative Pose During Satellite Proximity Operations, Scott J. Kelly
Theses and Dissertations
Automated satellite proximity operations is an increasingly relevant area of mission operations for the US Air Force with potential to significantly enhance space situational awareness (SSA). Simultaneous localization and mapping (SLAM) is a computer vision method of constructing and updating a 3D map while keeping track of the location and orientation of the imaging agent inside the map. The main objective of this research effort is to design a monocular SLAM method customized for the space environment. The method developed in this research will be implemented in an indoor proximity operations simulation laboratory. A run-time analysis is performed, showing near …
Terrain Referenced Navigation Using Sift Features In Lidar Range-Based Data, Matthew T. Leines
Terrain Referenced Navigation Using Sift Features In Lidar Range-Based Data, Matthew T. Leines
Theses and Dissertations
The use of GNSS in aiding navigation has become widespread in aircraft. The long term accuracy of INS are enhanced by frequent updates of the highly precise position estimations GNSS provide. Unfortunately, operational environments exist where constant signal or the requisite number of satellites are unavailable, significantly degraded, or intentionally denied. This thesis describes a novel algorithm that uses scanning LiDAR range data, computer vision features, and a reference database to generate aircraft position estimations to update drifting INS estimates. The algorithm uses a single calibrated scanning LiDAR to sample the range and angle to the ground as an aircraft …
Enhanced Image-Aided Navigation Algorithm With Automatic Calibration And Affine Distortion Prediction, Juan D. Jurado
Enhanced Image-Aided Navigation Algorithm With Automatic Calibration And Affine Distortion Prediction, Juan D. Jurado
Theses and Dissertations
This research aims at improving two key steps within the image aided navigation process: camera calibration and landmark tracking. The camera calibration step is improved by automating the point correspondence calculation within the standard camera calibration algorithm, thereby reducing the required time for calibration while maintaining the output model accuracy. The feature landmark tracking step is improved by digitally simulating affine distortions on input images in order to calculate more accurate feature descriptors for improved feature matching in high relative viewpoint change. These techniques are experimentally demonstrated in an outdoor environment with a consumer-grade inertial sensor and three imaging sensors, …
Enhancement Technique For Aerial Images, Sertan Erkanli, Ahmet Gungor Pakfiliz, Jiang Li
Enhancement Technique For Aerial Images, Sertan Erkanli, Ahmet Gungor Pakfiliz, Jiang Li
Electrical & Computer Engineering Faculty Publications
Recently, we proposed an enhancement technique for uniformly and non-uniformly illuminated dark images that provides high color accuracy and better balance between the luminance and the contrast in images to improve the visual representations of digital images. In this paper we define an improved version of the proposed algorithm to enhance aerial images in order to reduce the gap between direct observation of a scene and its recorded image.
Deeply-Integrated Feature Tracking For Embedded Navigation, Jeffery R. Gray
Deeply-Integrated Feature Tracking For Embedded Navigation, Jeffery R. Gray
Theses and Dissertations
The Air Force Institute of Technology (AFIT) is investigating techniques to improve aircraft navigation using low-cost imaging and inertial sensors. Stationary features tracked within the image are used to improve the inertial navigation estimate. These features are tracked using a correspondence search between frames. Previous research investigated aiding these correspondence searches using inertial measurements (i.e., stochastic projection). While this research demonstrated the benefits of further sensor integration, it still relied on robust feature descriptors (e.g., SIFT or SURF) to obtain a reliable correspondence match in the presence of rotation and scale changes. Unfortunately, these robust feature extraction algorithms are computationally …
Model-Based Control Using Model And Mechanization Fusion Techniques For Image-Aided Navigation, Constance D. Hendrix
Model-Based Control Using Model And Mechanization Fusion Techniques For Image-Aided Navigation, Constance D. Hendrix
Theses and Dissertations
Unmanned aerial vehicles are no longer used for just reconnaissance. Current requirements call for smaller autonomous vehicles that replace the human in high-risk activities. Many times these activities are performed in GPS-degraded environments. Without GPS providing today's most accurate navigation solution, autonomous navigation in tight areas is more difficult. Today, image-aided navigation is used and other methods are explored to more accurately navigate in such areas (e.g., indoors). This thesis explores the use of inertial measurements and navigation solution updates using cameras with a model-based Linear Quadratic Gaussian controller. To demonstrate the methods behind this research, the controller will provide …
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 …
Communication Free Robot Swarming, Zachary C. Gray
Communication Free Robot Swarming, Zachary C. Gray
Theses and Dissertations
As the military use of unmanned aerial vehicles increases, a growing need for novel strategies to control these systems exists. One such method for controlling many unmanned aerial vehicles simultaneously is the through the use of swarm algorithms. This research explores a swarm robotic algorithm developed by Kadrovach implemented on Pioneer Robots in a real-world environment. An adaptation of his visual sensor is implemented using stereo vision as the primary method of sensing the environment. The swarm members are prohibited from explicitly communicating other than passively through the environment. The resulting implementation produces a communication free swarming algorithm. The algorithm …
Seasonal Adaptation Of Vegetation Color In Satellite Images, Srinivas Jakkula, Vamsi K.R. Mantena, Ramu Pedada, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)
Seasonal Adaptation Of Vegetation Color In Satellite Images, Srinivas Jakkula, Vamsi K.R. Mantena, Ramu Pedada, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)
Electrical & Computer Engineering Faculty Publications
Remote sensing techniques like NDVI (Normal Difference vegetative Index) when applied to phenological variations in aerial images, ascertained the seasonal rise and decline of photosynthetic activity in different seasons, resulting in different color tones of vegetation. The rise and fall of NDVI values decide the biological response, either the green up or brown down [1]. Vegetation in green up period appears with more vegetative vigor and during brown down period it has a dry appearance. This paper proposes a novel method that identifies vegetative patterns in satellite images and then alters vegetation color to simulate seasonal changes based on training …
Situational Awareness And Synthetic Vision For Unmanned Aerial Vehicle Flight Testing, Joseph M. Dugan
Situational Awareness And Synthetic Vision For Unmanned Aerial Vehicle Flight Testing, Joseph M. Dugan
Theses and Dissertations
The Advanced Navigation Technology (ANT) Center at the Air Force Institute of Technology (AFIT) is currently exploring ways to develop and advance the employment of autonomous Unmanned Aerial Vehicles (UAV) by the Department of Defense for military purposes. The research in this thesis describes the development of a tool that enhances situational awareness and provides synthetic vision in a program called the Aviator Visual Display Simulator (AVDS) during UAV flight. During flight testing, the Situational Awareness and Synthetic Vision Relay Tool (SASVRT) developed provides the test coordinator and pilot, as well as the safety observers, with the most pertinent information …