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Full-Text Articles in Engineering
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.
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.
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.
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.
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).
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.
Unmanned Air Vehicle Testbed For Cooperative Control Experiments, Timothy W. Mclain, Randal W. Beard
Unmanned Air Vehicle Testbed For Cooperative Control Experiments, Timothy W. Mclain, Randal W. Beard
Faculty Publications
This paper describes the MAGICC Lab unmanned air vehicle (UAV) testbed at Brigham Young University. Motivation for pursuing experimental research with UAVs is given as well as a historical perspective of the UAV testbed development. Lessons learned through the development and use of the testbed over the past several years are summarized.
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.
Autonomous Vehicle Technologies For Small Fixed Wing Uavs, Derek B. Kingston, Randal Beard, Timothy Mclain, Michael Larsen, Wei Ren
Autonomous Vehicle Technologies For Small Fixed Wing Uavs, Derek B. Kingston, Randal Beard, Timothy Mclain, Michael Larsen, Wei Ren
Faculty Publications
Autonomous unmanned air vehicle flight control systems require robust path generation to account for terrain obstructions, weather, and moving threats such as radar, jammers, and unfriendly aircraft. In this paper, we outline a feasible, hierarchal approach for real-time motion planning of small autonomous fixed-wing UAVs. The approach divides the trajectory generation into four tasks: waypoint path planning, dynamic trajectory smoothing, trajectory tracking, and low-level autopilot compensation. The waypoint path planner determines the vehicle's route without regard for the dynamic constraints of the vehicle. This results in a significant reduction in the path search space, enabling the generation of complicated paths …
Cooperative Path Planning For Timing Critical Missions, Timothy W. Mclain, Randal W. Beard
Cooperative Path Planning For Timing Critical Missions, Timothy W. Mclain, Randal W. Beard
Faculty Publications
This paper presents a cooperative path planning approach for teams of vehicles operating under timing constraints. A cooperative control approach based on coordination variables and coordination functions is introduced and applied to cooperative timing problems. Three types of timing constraints are considered: simultaneous arrival, tight sequencing, and loose sequencing. Simulation results demonstrating the approach are presented.
Experimental Demonstration Of Multiple Robot Cooperative Target Intercept, Timothy W. Mclain, Randal W. Beard, Jed M. Kelsey
Experimental Demonstration Of Multiple Robot Cooperative Target Intercept, Timothy W. Mclain, Randal W. Beard, Jed M. Kelsey
Faculty Publications
This paper presents experimental results for the simultaneous intercept of preassigned targets by a team of mobile robots. The robots are programmed to mimic the dynamic behavior of unmanned air vehicles in constant-altitude flight. In proceeding to their targets, robots must avoid both known static threats and pop-up threats. An overview of the cooperative control strategy followed is given, as well as a description of the robot hardware and software used. Experimental results demonstrating simultaneous intercept of targets by the robot team are presented.
Cooperative Control Of Uav Rendezvous, Timothy W. Mclain, Phillip R. Chandler, Steven Rasmussen, Meir Pachter
Cooperative Control Of Uav Rendezvous, Timothy W. Mclain, Phillip R. Chandler, Steven Rasmussen, Meir Pachter
Faculty Publications
The cooperative control of timing and synchronization of tasks of multiple unmanned air vehicles (UAVs) represents a valuable capability for a wide range of potential multi-UAV missions. This research addresses the specific problem of cooperative rendezvous in which multiple UAVs are to arrive at their targets simultaneously. The development of a rendezvous manager state machine and a cooperative control decomposition approach are described. Simulation results demonstrating the feasibility of the approach are presented.