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Author: Publisher: ISBN: Category : Languages : en Pages : 9
Book Description
In this paper, a strategy for an autonomous landing maneuver for an under-actuated, unmanned aerial vehicle (UAV) using position information obtained from a single monocular on-board camera is presented. Although the UAV is underactuated in translational control inputs (i.e., a lift force can only be produced), the proposed controller is shown to achieve globally uniform ultimate boundedness (GUUB) in position regulation error during the landing approach. The proposed vision-based control algorithm is built upon homography-based techniques and Lyapunov design methods.
Author: Publisher: ISBN: Category : Languages : en Pages : 9
Book Description
In this paper, a strategy for an autonomous landing maneuver for an under-actuated, unmanned aerial vehicle (UAV) using position information obtained from a single monocular on-board camera is presented. Although the UAV is underactuated in translational control inputs (i.e., a lift force can only be produced), the proposed controller is shown to achieve globally uniform ultimate boundedness (GUUB) in position regulation error during the landing approach. The proposed vision-based control algorithm is built upon homography-based techniques and Lyapunov design methods.
Author: Paul A. Ghyzel Publisher: ISBN: 9781423533214 Category : Languages : en Pages : 128
Book Description
The role of Unmanned Aerial Vehicles (UAV) for modern military operations is expected to expand in the 21st Century, including increased deployment of UAVs from Navy ships at sea. Autonomous operation of UAVs from ships at sea requires the UAV to land on a moving ship using only passive sensors installed in the UAV. This thesis investigates the feasibility of using passive vision sensors installed in the UAV to estimate the UAV position relative to the moving platform. A navigation algorithm based on photogrammetry and perspective estimation is presented for numerically determining the relative position and orientation of an aircraft with respect to a ship that possesses three visibly significant points with known separation distances. Original image processing algorithms that reliably locate visually significant features in monochrome images are developed. Monochrome video imagery collected during flight test with an infrared video camera mounted in the nose of a UAV during actual landing approaches is presented. The navigation and image processing algorithms are combined to reduce the flight test images into vehicle position estimates. These position estimates are compared to truth data to demonstrate the feasibility of passive, vision-based sensors for aircraft navigation. Conclusions are drawn, and recommendations for further study are presented.
Author: Joshua Hintze Publisher: ISBN: Category : Computer vision Languages : en Pages : 59
Book Description
Landing an Unmanned Aerial Vehicle (UAV) is a non-trivial problem. Removing the ability to cooperate with the landing site further increases the complexity. This thesis develops a multi-stage process that allows a UAV to locate the safest landing site, and then land without a georeference. Machine vision is the vehicle sensor used to locate potential landing hazards and generate an estimated UAV position. A description of the algorithms, along with validation results, are presented. The thesis shows that software-simulated landing performs adequately, and that future hardware integration looks promising.
Author: Iryna Borshchova Publisher: ISBN: Category : Languages : en Pages :
Book Description
A hybrid-like (continuous and discrete-event) approach to controlling a small multi-rotor unmanned aerial system (UAS) while landing on a moving platform is described. The landing scheme is based on positioning visual markers on a landing platform in a detectable pattern. After the onboard camera detects the object pattern, the inner control algorithm sends visual-based servo-commands to align the multi-rotor with the targets. This method is less computationally complex as it uses color-based object detection applied to a geometric pattern instead of feature tracking algorithms, and has the advantage of not requiring the distance to the objects to be calculated. The continuous approach accounts for the UAV and the platform rolling/pitching/yawing, which is essential for a real-time landing on a moving target such as a ship. A discrete-event supervisor working in parallel with the inner controller is designed to assist the automatic landing of a multi-rotor UAV on a moving target. This supervisory control strategy allows the pilot and crew to make time-critical decisions when exceptions, such as losing targets from the field of view, occur. The developed supervisor improves the low-level vision-based auto-landing system and high-level human-machine interface. The proposed hybrid-like approach was tested in simulation using a quadcopter model in Virtual Robotics Experimentation Platform (V-REP) working in parallel with Robot Operating System (ROS). Finally, this method was validated in a series of real-time experiments with indoor and outdoor quadcopters landing on both static and moving platforms. The developed prototype system has demonstrated the capability of landing within 25 cm of the desired point of touchdown. This auto-landing system is small (100 x 100 mm), light-weight (100 g), and consumes little power (under 2 W).
Author: Nicholas Quatrociocchi Publisher: ISBN: Category : Computer vision Languages : en Pages : 0
Book Description
"High traffic congestion in cities can lead to difficulties in delivering appropriate aid to people in need of emergency services. Developing an autonomous aerial medical evacuation system with the required size to facilitate the need can allow for the mitigation of the constraint. The aerial system must be capable of vertical takeoff and landing to reach highly conjected areas and areas where traditional aircraft cannot access. In general, the most challenging limitation within any proposed solution is the landing sequence. There have been several techniques developed over the years to land aircraft autonomously; however, very little attention has been scoped to operate strictly within highly congested urban-type environments. The goal of this research is to develop a possible solution to achieve autonomous landing based on computer vision-capture systems. For example, by utilizing modern computer vision approaches involving depth estimation through binocular stereo computer vision, a depth map can be developed. If the vision system is mounted to the bottom of an autonomous aerial system, it can represent the area below the aircraft and determine a possible landing zone. In this work, neural networks are used to isolate the ground via the computer vision height map. Then out of the entire visible ground area, a potential landing position can be estimated. An optimization routine is then developed to identify the most optimal landing position within the visible area. The optimization routine identifies the largest identifiable open area near the desired landing location. Web cameras were utilized and processed on a desktop to form a basis for the computer vision system. The algorithms were tested and verified using a simulation effort proving the feasibility of the approach. In addition, the system was tested on a scaled down city scene and was able to determine an optimal landing zone."--Abstract.
Author: Dale D. Rowley Publisher: ISBN: Category : Drone aircraft Languages : en Pages : 129
Book Description
Landing a rotorcraft unmanned aerial vehicle (RUAV) without human supervision is a capability that would significantly broaden the usefulness of UAVs. The benefits are even greater if the functionality is expanded to involve landing sites with unknown terrain and a lack of GPS or other positioning aids. Examples of these types of non-cooperative environments could range from remote mountainous regions to an urban building rooftop or a cluttered parking lot.
Author: Xiaolong Li Publisher: Springer Nature ISBN: 3030810070 Category : Technology & Engineering Languages : en Pages : 1317
Book Description
This book presents select proceedings of the International Conference on Intelligent Automation and Soft Computing (IASC2021). Various topics covered in this book include AI algorithm, neural networks, pattern recognition, machine learning, blockchain technology, system engineering, computer vision and image processing, adaptive control and robotics, big data and data processing, networking and security. The book is a valuable reference for beginners, researchers, and professionals interested in artificial intelligence, automation, and soft computing.
Author: Kimon P. Valavanis Publisher: Springer Science & Business Media ISBN: 1402061145 Category : Technology & Engineering Languages : en Pages : 552
Book Description
The past decade has seen tremendous interest in the production and refinement of unmanned aerial vehicles, both fixed-wing, such as airplanes and rotary-wing, such as helicopters and vertical takeoff and landing vehicles. This book provides a diversified survey of research and development on small and miniature unmanned aerial vehicles of both fixed and rotary wing designs. From historical background to proposed new applications, this is the most comprehensive reference yet.
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Author: 
Author: Paul A. Ghyzel
Author: Courtney S. Sharp
Author: Joshua Hintze
Author: Iryna Borshchova
Author: Nicholas Quatrociocchi
Author: Dale D. Rowley
Author: Martin D. Levine
Author: Xiaolong Li
Author: Kimon P. Valavanis