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Full-Text Articles in Mechanical Engineering
Uav Rapidly-Deployable Stage Sensor With Electro-Permanent Magnet Docking Mechanism For Flood Monitoring In Undersampled Watersheds, Corinne A, Smith, Joud Satme, Jacob Martin, Austin Downey, Nikolaos Vitzilaios, Jasim Imran
Uav Rapidly-Deployable Stage Sensor With Electro-Permanent Magnet Docking Mechanism For Flood Monitoring In Undersampled Watersheds, Corinne A, Smith, Joud Satme, Jacob Martin, Austin Downey, Nikolaos Vitzilaios, Jasim Imran
Faculty Publications
The availability of historical flood data is vital in recognizing weather-related trends and outlining necessary precautions for at-risk communities. Flood frequency, magnitude, endurance, and volume are traditionally recorded using established streamgages; however, the material and installation costs allow only a few streamgages in a region, which yield a narrow data selection. In particular, stage, the vertical water height in a water body, is an important parameter in determining flood trends. This work investigates a low-cost, compact, rapidly-deployable alternative to traditional stage sensors that will allow for denser sampling within a watershed and a more detailed record of flood events. The …
Dynamic Optimization Of High-Altitude Solar Aircraft Trajectories Under Station-Keeping Constraints, Abraham Martin, Nathaniel Gates, Andrew Ning, John Hedengren
Dynamic Optimization Of High-Altitude Solar Aircraft Trajectories Under Station-Keeping Constraints, Abraham Martin, Nathaniel Gates, Andrew Ning, John Hedengren
Faculty Publications
This paper demonstrates the use of nonlinear dynamic optimization to calculate energy- optimal trajectories for a high-altitude, solar-powered Unmanned Aerial Vehicle (UAV). The objective is to maximize the total energy in the system while staying within a 3 km mission radius and meeting other system constraints. Solar energy capture is modeled using the vehicle orientation and solar position, and energy is stored both in batteries and in potential energy through elevation gain. Energy capture is maximized by optimally adjusting the angle of the aircraft surface relative to the sun. The UAV flight and energy system dynamics are optimized over a …
Deep Visual Gravity Vector Detection For Unmanned Aircraft Attitude Estimation, Gary J. Ellingson, David Wingate, Tim Mclain
Deep Visual Gravity Vector Detection For Unmanned Aircraft Attitude Estimation, Gary J. Ellingson, David Wingate, Tim Mclain
Faculty Publications
This paper demonstrates a feasible method for using a deep neural network as a sensor to estimate the attitude of a flying vehicle using only flight video. A dataset of still images and associated gravity vectors was collected and used to perform supervised learning. The network builds on a previously trained network and was trained to be able to approximate the attitude of the camera with an average error of about 8 degrees. Flight test video was recorded and processed with a relatively simple visual odometry method. The aircraft attitude is then estimated with the visual odometry as the state …
Rosflight: A Lightweight, Inexpensive Mav Research And Development Tool, Timothy Mclain, James Jackson, Gary J. Ellingson
Rosflight: A Lightweight, Inexpensive Mav Research And Development Tool, Timothy Mclain, James Jackson, Gary J. Ellingson
Faculty Publications
To accelerate research and development of the autonomous capabilities of micro aerial vehicles we have developed flight control framework, ROSflight, as a research tool. ROSflight makes development of autopilot code easier and more efficient by minimizing the use of embedded systems, incorporating the Robot Operating System and using off-the-shelf and open-source hardware and software. Motivation and applications for use in the research community are discussed. Analysis of loop rate and communication bandwidth are presented as well as results from flight demonstration of two multi-rotor aircraft.
Non-Redundant Sensor Fault Detection Using An Improved Dynamic Model, Brandon Cannon, Robert C. Leishman, Timothy W. Mclain, Joseph Jackson, Jovan Boskovic
Non-Redundant Sensor Fault Detection Using An Improved Dynamic Model, Brandon Cannon, Robert C. Leishman, Timothy W. Mclain, Joseph Jackson, Jovan Boskovic
Faculty Publications
This paper proposes a method of detecting faults in non-redundant sensors. Such a method is advantageous for small unmanned aerial vehicles (UAVs), which are prevented from carrying redundant sensors due to size, weight, and power constraints. The method we propose uses a multiplicative extended Kalman lter (MEKF) for estimation and employs hypothesis testing to detect faults. This method has been shown to detect bias, drift, and increased noise in a non-redundant sensor real-time on board an autonomous rotorcraft.
Robust Motion Estimation With Rgb-D Cameras, Robert C. Leishman, Daniel Koch, Timothy W. Mclain
Robust Motion Estimation With Rgb-D Cameras, Robert C. Leishman, Daniel Koch, Timothy W. Mclain
Faculty Publications
Estimating vehicle motion using vision sensors in real time has been greatly explored in the past few years due to speed improvements and advances in computer hardware. Six degree of freedom motion estimation using vision information is desirable due to a vision sensors low cost, low power requirements and light weight and for the quality of the solutions that can be obtained using few assumptions about the environment. However, cameras have the downside of not providing good estimates when visual features are sparse or not available. Also, there are problems with changes in lighting and when light is low or …
Energy Harvesting And Mission Effectiveness For Small Unmanned Air Vehicles, Mark J. Cutler, Timothy W. Mclain, Randal W. Beard, Brian Capozzi
Energy Harvesting And Mission Effectiveness For Small Unmanned Air Vehicles, Mark J. Cutler, Timothy W. Mclain, Randal W. Beard, Brian Capozzi
Faculty Publications
This paper explores the feasibility of improving unmanned air vehicle (UAV) mission effectiveness by extracting energy from the atmosphere. Specifically, we consider an aerial surveillance mission in the vicinity of a geographic ridge. Cross winds owing over the ridge produce regions of lift on the windward side that can be exploited to increase mission duration. Mission effectiveness is quantified using the seeability metric. Simulation results are presented for several observation target placements. Results indicate that seeability and imaging persistence can be improved by exploiting ridge lift. Simulations demonstrated that targets at ranges less than four times the ridge height were …
Performance Flight Testing Of Small Electric Powered Unmanned Aerial Vehicles, Jon N. Ostler, W. Jerry Bowman, Deryl O. Snyder, Timothy W. Mclain
Performance Flight Testing Of Small Electric Powered Unmanned Aerial Vehicles, Jon N. Ostler, W. Jerry Bowman, Deryl O. Snyder, Timothy W. Mclain
Faculty Publications
Flight testing methods are developed to find the drag polar for small unmanned aerial vehicles powered by electric motors with fixed-pitch propellers. Wind tunnel testing was used to characterize the propeller-motor efficiency. The drag polar was constructed using data from flight tests. This drag polar was then used to find the following performance parameters: maximum velocity, minimum velocity, velocity for maximum range, velocity for maximum endurance, maximum rate of climb, maximum climb angle, minimum turn radius, maximum turn rate, and maximum bank angle. The developed flight testing methods are used to characterize the performance of a small UAV.
Dynamics And Control Of Cable-Drogue System In Aerial Recovery Of Micro Air Vehicles Based On Gauss's Principle, Liang Sun, Randal W. Beard, Mark B. Colton, Timothy W. Mclain
Dynamics And Control Of Cable-Drogue System In Aerial Recovery Of Micro Air Vehicles Based On Gauss's Principle, Liang Sun, Randal W. Beard, Mark B. Colton, Timothy W. Mclain
Faculty Publications
This paper presents a new concept for aerial recovery of Micro Air Vehicles (ARMAVs) using a large mothership and a recovery drogue. The mothership drags a drogue attached to a cable and the drogue is controlled to match the flight patten of the MAV. This paper uses Gauss’s Principle to derive the dynamic model of the cable-drogue systems. A controllable drogue plays a key role in recovering MAVs in windy conditions. We develop a control approach for the drogue using its drag coefficient. Simulation results based on multilink cable-drogue systems present the feasibility of the aerial recovery concept and the …
Payload Directed Flight Of Miniature Air Vehicles, Randal W. Beard, Clark Taylor, Jeff Saunders, Ryan Holt, Timothy W. Mclain
Payload Directed Flight Of Miniature Air Vehicles, Randal W. Beard, Clark Taylor, Jeff Saunders, Ryan Holt, Timothy W. Mclain
Faculty Publications
This paper describes three applications of payload directed flight using miniature air vehicles: vision-based road following, vision-based target tracking, and vision-based mapping. A general overview of each application is given, followed by simulation and flight-test results. Results demonstrate the viability of utilizing electo-optical video imagery to directly control the air vehicle flight path to enhance performance relative to the sensing objective.
Aerobatic Maneuvering Of Miniature Air Vehicles Using Attitude Trajectories, James K. Hall, Timothy W. Mclain
Aerobatic Maneuvering Of Miniature Air Vehicles Using Attitude Trajectories, James K. Hall, Timothy W. Mclain
Faculty Publications
We develop aerobatic maneuvering for miniature air vehicles (MAVs) using time-parameterized attitude trajectory generation and an associated attitude tracking control law. We develop two methodologies, polynomial or trigonometric, for creating smooth functions that specify pitch and roll angle trajectories. For both approaches, the functions are constrained by the maneuver boundary conditions for aircraft position and velocity. We develop a feedback control law to regulate aircraft orientation throughout the maneuvers. The performance of our trajectory generation algorithm and our attitude tracking control law is demonstrated through simulated and actual flight tests of aerobatic maneuvers.
Experiments In Cooperative Timing For Miniature Air Vehicles, Derek R. Nelson, Timothy W. Mclain, Randal W. Beard
Experiments In Cooperative Timing For Miniature Air Vehicles, Derek R. Nelson, Timothy W. Mclain, Randal W. Beard
Faculty Publications
This paper presents experimental results for two cooperative timing missions carried out using a team of three miniature air vehicles (MAVs). Using a cooperative timing algorithm based on coordination functions and coordination variables, the MAV team executed a series of simultaneous arrival and cooperative fly-by missions. In the presence of significant wind disturbances, the average time difference between the first and last vehicle in the simultaneous arrival experiments was 1.6 s. For the cooperative fly-by experiments, the average timing error between vehicle arrivals was 0.6 s. These results demonstrate the practical feasibility of the cooperative timing approach.
Obstacle Avoidance Using Circular Paths, Timothy Mclain, Randal W. Beard, Jeffery Brian Saunders
Obstacle Avoidance Using Circular Paths, Timothy Mclain, Randal W. Beard, Jeffery Brian Saunders
Faculty Publications
This paper develops a method of obstacle avoidance for fixed-wing miniature air vehicles (MAV) using a series of circular oscillating paths and a single point laser ranger. The laser ranger is a low power, light-weight device used to report the distance to an object in a single direction of the body frame of a MAV. The oscillating paths allow the laser ranger to scan for obstacles and possible escape paths for the MAV in the case of obstacle detection. The circular paths are generated along waypoint paths and transition between waypoint paths without loss of scanning capabilities. Obstacle avoidance is …
Probabilistic Searching Using A Small Unmanned Aerial Vehicle, Steven R. Hansen, Timothy W. Mclain, Michael A. Goodrich
Probabilistic Searching Using A Small Unmanned Aerial Vehicle, Steven R. Hansen, Timothy W. Mclain, Michael A. Goodrich
Faculty Publications
Ground breaking concepts in optimal search theory were developed during World War II by the U.S. Navy. These concepts use an assumed detection model to calculate a detection probability rate and an optimal search allocation. Although this theory is useful in determining when and where search effort should be applied, it offers little guidance for the planning of search paths. This paper explains how search theory can be applied to path planning for an SUAV with a fixed CCD camera. Three search strategies are developed: greedy search, contour search, and composite search. In addition, the concepts of search efficiency and …
Autonomous Landing Of Miniature Aerial Vehicles, D. Blake Barber, Stephen R. Griffiths, Timothy W. Mclain, Randal W. Beard
Autonomous Landing Of Miniature Aerial Vehicles, D. Blake Barber, Stephen R. Griffiths, Timothy W. Mclain, Randal W. Beard
Faculty Publications
This paper outlines an approach for automated landing of miniature aerial vehicles (MAVs). A landing algorithm defining the landing flight path as a function of height above ground, and the control strategies for following the path, are described. Two methods are presented for estimating height above ground, one based on barometric pressure measurements and the other utilizing optic-flow measurements. The development of an optic-flow sensor and associated sampling strategies are described. Utilizing estimates of height above ground from barometric pressure and optic-flow measurements, repeated landings were performed with a 1.5 m wingspan MAV. With height above ground estimated from barometric …
Vision-Based Landing Of Fixed-Wing Miniature Air Vehicles, Blake Barber, Timothy Mclain, Barrett Edwards
Vision-Based Landing Of Fixed-Wing Miniature Air Vehicles, Blake Barber, Timothy Mclain, Barrett Edwards
Faculty Publications
This paper outlines a method for using vision-based feedback to accurately land a MAV on a visually identifiable target of approximately known location. The method presented is robust to wind, capable of handling both stationary and moving targets, and capable of cor- recting for camera misalignment, state estimation biases, and parameter estimation biases. Landing results from actual flight tests are presented which demonstrate the effectiveness of the proposed method.
An Overview Of Mav Research At Brigham Young University, Timothy W. Mclain, Randal W. Beard, D. Blake Barber, Nathan B. Knoebel
An Overview Of Mav Research At Brigham Young University, Timothy W. Mclain, Randal W. Beard, D. Blake Barber, Nathan B. Knoebel
Faculty Publications
This paper summarizes research efforts at Brigham Young University related to the control of miniature aerial vehicles (MAVs). Recent results in the areas of vector field path following, precision landing and target prosecution, target localization, obstacle detection and avoidance, tailsitter aircraft control, and cooperative control are presented.
Vision-Based Target Geo-Location Using A Fixed-Wing Miniature Air Vehicle, D. Blake Barber, Joshua D. Redding, Timothy W. Mclain, Randal W. Beard, Clark N. Taylor
Vision-Based Target Geo-Location Using A Fixed-Wing Miniature Air Vehicle, D. Blake Barber, Joshua D. Redding, Timothy W. Mclain, Randal W. Beard, Clark N. Taylor
Faculty Publications
This paper presents a method for determining the GPS location of a ground-based object when imaged from a fixed-wing miniature air vehicle (MAV). Using the pixel location of the target in an image, with measurements of MAV position and attitude, and camera pose angles, the target is localized in world coordinates. The main contribution of this paper is to present four techniques for reducing the localization error. In particular, we discuss RLS filtering, bias estimation, flight path selection, and wind estimation. The localization method has been implemented and flight tested on BYU’s MAV testbed and experimental results are presented demonstrating …
Maximizing Miniature Aerial Vehicles, Stephen Griffiths, Jeffery Brian Saunders, Andrew Curtis, Blake Barber, Timothy W. Mclain, Randal W. Beard
Maximizing Miniature Aerial Vehicles, Stephen Griffiths, Jeffery Brian Saunders, Andrew Curtis, Blake Barber, Timothy W. Mclain, Randal W. Beard
Faculty Publications
Despite the tremendous potential demonstrated by miniature aerial vehicles (MAV) in numerous applications, they are currently limited to operations in open air space, far away from obstacles and terrain. To broaden the range of applications for MAVs, methods to enable operation in environments of increased complexity must be developed. In this article, we presented two strategies for obstacle and terrain avoidance that provide a means for avoiding obstacles in the flight path and for staying centered in a winding corridor.
Vision-Based Target Localization From A Fixed-Wing Miniature Air Vehicle, Joshua D. Redding, Timothy W. Mclain, Randal W. Beard, Clark N. Taylor
Vision-Based Target Localization From A Fixed-Wing Miniature Air Vehicle, Joshua D. Redding, Timothy W. Mclain, Randal W. Beard, Clark N. Taylor
Faculty Publications
This paper presents a method for localizing a ground-based object when imaged from a small fixed-wing unmanned aerial vehicle (UAV). Using the pixel location of the target in an image, with measurements of UAV position and attitude, and camera pose angles, the target is localized in world coordinates. This paper presents a study of possible error sources and localization sensitivities to each source. The localization method has been implemented and experimental results are presented demonstrating the localization of a target to within 11 m of its known location.
Vector Field Path Following For Small Unmanned Aerial Vehicles, Derek R. Nelson, D. Blake Barber, Timothy W. Mclain, Randal W. Beard
Vector Field Path Following For Small Unmanned Aerial Vehicles, Derek R. Nelson, D. Blake Barber, Timothy W. Mclain, Randal W. Beard
Faculty Publications
This paper presents a new method for unmanned aerial vehicle path following using vector fields to represent desired ground track headings to direct the vehicle onto the desired path. The key feature of this approach is that ground track heading error and lateral following error approach zero asymptotically even in the presence of constant wind disturbances. Methods for following straight-line and circularorbit paths, as well as combinations of straight lines and arcs, are presented. Experimental results validate the effectiveness of this path following approach for small air vehicles flying in high-wind conditions.
Forest Fire Monitoring Using Multiple Unmanned Air Vehicles, Timothy Mclain, Randal W. Beard, Ryan S. Holt, Joseph W. Egbert, Justin M. Bradley, Clark N. Taylor
Forest Fire Monitoring Using Multiple Unmanned Air Vehicles, Timothy Mclain, Randal W. Beard, Ryan S. Holt, Joseph W. Egbert, Justin M. Bradley, Clark N. Taylor
Faculty Publications
The ability to gather and process information on the condition of forest fires is essential to fighting the fires in a cost-effective, safe, and efficient manner. While high-altitude, long-endurance (HALE) unmanned air vehicles (UAVs) are currently used for fire surveillance; they are an expensive and scarce resource. As a proposed alternative, low-altitude, short-endurance (LASE) UAVs offer lower costs, quicker response times, and high- resolution information. In recent years, advances in solid-state sensor and autopilot technology have made LASE UAVs a feasible alternative. This paper overviews a current research project conducted by Brigham Young University and NASA Ames. In the project, …
Learning Real-Time A* Path Planner For Unmanned Air Vehicle Target Sensing, Jason K. Howlett, Timothy W. Mclain, Michael A. Goodrich
Learning Real-Time A* Path Planner For Unmanned Air Vehicle Target Sensing, Jason K. Howlett, Timothy W. Mclain, Michael A. Goodrich
Faculty Publications
This paper presents a path planner for sensing closely-spaced targets from a fixed-wing unmanned air vehicle (UAV) having a specified sensor footprint. The planner is based on the learning real-time A* (LRTA*) search algorithm and produces dynamically feasible paths that accomplish the sensing objectives in the shortest possible distance. A tree of candidate paths that span the area of interest is created by assembling primitive turn and straight sections of a specified step size in a sequential fashion from the starting position of the UAV. An LRTA* search of the tree produces feasible paths any time during its execution and …
Static And Dynamic Obstacle Avoidance For Miniature Air Vehicles, Jeffery Brian Saunders, Brandon Call, Andrew Curtis, Randal W. Beard, Timothy W. Mclain
Static And Dynamic Obstacle Avoidance For Miniature Air Vehicles, Jeffery Brian Saunders, Brandon Call, Andrew Curtis, Randal W. Beard, Timothy W. Mclain
Faculty Publications
Small unmanned air vehicles are limited in sensor weight and power such that detection and avoidance of unknown obstacles during flight is difficult. This paper presents a low power low weight method of detection using a laser range finder. In addition, a rapidly-exploring random tree algorithm to generate waypoint paths around obstacles known a priori is presented, and a dynamic geometric algorithm to generate paths around detected obstacles is derived. The algorithms are demonstrated in simulation and in flight tests on a fixed-wing miniature air vehicle (MAV).
Decentralized Perimeter Surveillance Using A Team Of Uavs, Timothy Mclain, Randal W. Beard, Derek Kingston, Ryan S. Holt, David W. Casbeer
Decentralized Perimeter Surveillance Using A Team Of Uavs, Timothy Mclain, Randal W. Beard, Derek Kingston, Ryan S. Holt, David W. Casbeer
Faculty Publications
This paper poses the cooperative perimeter-surveillance problem and offers a decentralized solution that accounts for perimeter growth (expanding or contracting) and insertion/deletion of team members. By identifying and sharing the critical coordination information and by exploiting the known communication topology, only a small communication range is required for accurate performance. Simulation and hardware results are presented that demonstrate the applicability of the solution.
Forest Fire Monitoring With Multiple Small Uavs, David W. Casbeer, Randal W. Beard, Timothy W. Mclain, Sai-Ming Li, Raman K. Mehra
Forest Fire Monitoring With Multiple Small Uavs, David W. Casbeer, Randal W. Beard, Timothy W. Mclain, Sai-Ming Li, Raman K. Mehra
Faculty Publications
Frequent and detailed updates of the development of a forest fire are essential for effective and safe fire fighting. Since a forest fire is typically inaccessible by ground vehicles due to mountainous terrain, small Unmanned Air Vehicles (UAVs) are emerging as a promising solution to the problem of monitoring large forest fires. In this paper we present an effective path planning algorithm for a UAV utilizing infrared images that are collected on-board in realtime. In order to demonstrate the effectiveness of our path planning algorithm in realistic scenarios, we implemented the forest fire propagation model EMBYR to simulate the time …
Autonomous Vehicle Technologies For Small Fixed-Wing Uavs, Randal Beard, Derek Kingston, Morgan Quigley, Deryl Snyder, Reed Christiansen, Walt Johnson, Timothy Mclain, Michael A. Goodrich
Autonomous Vehicle Technologies For Small Fixed-Wing Uavs, Randal Beard, Derek Kingston, Morgan Quigley, Deryl Snyder, Reed Christiansen, Walt Johnson, Timothy Mclain, Michael A. Goodrich
Faculty Publications
The objective of this paper is to describe the design and implementation of a small semi-autonomous fixed-wing unmanned air vehicle. In particular we describe the hardware and software architectures used in the design. We also describe a low weight, low cost autopilot developed at Brigham Young University and the algorithms associated with the autopilot. Novel PDA and voice interfaces to the UAV are described. In addition, we overview our approach to real-time path planning, trajectory generation, and trajectory tracking. The paper is augmented with movie files that demonstrate the functionality of the UAV and its control software.
Initial Experiments In The Cooperative Control Of Unmanned Air Vehicles, Derek R. Nelson, Timothy W. Mclain, Reed S. Christiansen, Randal W. Beard, David Johansen
Initial Experiments In The Cooperative Control Of Unmanned Air Vehicles, Derek R. Nelson, Timothy W. Mclain, Reed S. Christiansen, Randal W. Beard, David Johansen
Faculty Publications
This paper addresses cooperative control for a team of unmanned air vehicles (UAVs). Specifically, a team of three small UAVs is controlled to perform a cooperative timing mission. Starting at loiter locations distributed around the periphery of a 2 km square battle area, the UAVs cooperatively plan paths to arrive at a target at the center of the battle area in sequence at 10 sec intervals. Cooperative path planning is performed using the methodology of coordination variables and coordination functions. Coordination and waypoint path planning are centralized on a ground station computer. Experiments have been performed using BYU’s fleet of …
Coordinated Uav Target Assignment Using Distributed Tour Calculation, David H. Walker, Timothy W. Mclain, Jason K. Kowlett
Coordinated Uav Target Assignment Using Distributed Tour Calculation, David H. Walker, Timothy W. Mclain, Jason K. Kowlett
Faculty Publications
In this chapter a method for assigning unmanned aerial vehicle agents to targets through the use of preplanned vehicle tours is presented. Assignments are based on multi-target tours that consider the spread of the targets and the sensor capabilities of the vehicles. In this way, the individual agents and the team as a whole make better use of team resources and improve team cooperation. Planning and assignments are accomplished in reasonable computational time through the use of heuristics to reduce the problem size.
Multiple Uav Cooperative Search Under Collision Avoidance And Limited Range Communication Constraints, Randal W. Beard, Timothy W. Mclain
Multiple Uav Cooperative Search Under Collision Avoidance And Limited Range Communication Constraints, Randal W. Beard, Timothy W. Mclain
Faculty Publications
This paper focuses on the problem of cooperatively searching, using a team of unmanned air vehicles (UAVs), an area of interest that contains regions of opportunity and regions of potential hazard. The objective of the UAV team is to visit as many opportunities as possible, while avoiding as many hazards as possible. To enable cooperation, the UAVs are constrained to stay within communication range of one another. Collision avoidance is also required. Algorithms for team-optimal and individually-optimal/team-suboptimal solutions are developed and their computational complexity compared. Simulation results demonstrating the feasibility of the cooperative search algorithms are presented.