Download or read book A Depth based Computer Vision Approach to Unmanned Aircraft System Landing with Optimal Positioning written by Nicholas Quatrociocchi and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.

Download or read book Imaging and Sensing for Unmanned Aircraft Systems written by Vania V. Estrela and published by Institution of Engineering and Technology. This book was released on 2020-02-01 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume book set explores how sensors and computer vision technologies are used for the navigation, control, stability, reliability, guidance, fault detection, self-maintenance, strategic re-planning and reconfiguration of unmanned aircraft systems (UAS). Volume 1 concentrates on UAS control and performance methodologies including Computer Vision and Data Storage, Integrated Optical Flow for Detection and Avoidance Systems, Navigation and Intelligence, Modeling and Simulation, Multisensor Data Fusion, Vision in Micro-Aerial Vehicles (MAVs), Computer Vision in UAV using ROS, Security Aspects of UAV and Robot Operating System, Vision in Indoor and Outdoor Drones, Sensors and Computer Vision, and Small UAV for Persistent Surveillance. Volume 2 focuses on UAS deployment and applications including UAV-CPSs as a Testbed for New Technologies and a Primer to Industry 5.0, Human-Machine Interface Design, Open Source Software (OSS) and Hardware (OSH), Image Transmission in MIMO-OSTBC System, Image Database, Communications Requirements, Video Streaming, and Communications Links, Multispectral vs Hyperspectral Imaging, Aerial Imaging and Reconstruction of Infrastructures, Deep Learning as an Alternative to Super Resolution Imaging, and Quality of Experience (QoE) and Quality of Service (QoS).

Download or read book Vision Based Navigation for Autonomous Landing of Unmanned Aerial Vehicles written by Paul A. Ghyzel and published by . This book was released on 2000-09-01 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Vision Based Systemsfor UAV Applications written by Aleksander Nawrat and published by Springer. This book was released on 2013-12-06 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is motivated by a significant number of vision based algorithms for Unmanned Aerial Vehicles (UAV) that were developed during research and development projects. Vision information is utilized in various applications like visual surveillance, aim systems, recognition systems, collision-avoidance systems and navigation. This book presents practical applications, examples and recent challenges in these mentioned application fields. The aim of the book is to create a valuable source of information for researchers and constructors of solutions utilizing vision from UAV. Scientists, researchers and graduate students involved in computer vision, image processing, data fusion, control algorithms, mechanics, data mining, navigation and IC can find many valuable, useful and practical suggestions and solutions. The latest challenges for vision based systems are also presented.

Download or read book Vision Assisted Landing of an Unmanned Aerial Vehicle written by and published by . This book was released on 2005 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Bio inspired Computation in Unmanned Aerial Vehicles written by Haibin Duan and published by Springer Science & Business Media. This book was released on 2014-01-02 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bio-inspired Computation in Unmanned Aerial Vehicles focuses on the aspects of path planning, formation control, heterogeneous cooperative control and vision-based surveillance and navigation in Unmanned Aerial Vehicles (UAVs) from the perspective of bio-inspired computation. It helps readers to gain a comprehensive understanding of control-related problems in UAVs, presenting the latest advances in bio-inspired computation. By combining bio-inspired computation and UAV control problems, key questions are explored in depth, and each piece is content-rich while remaining accessible. With abundant illustrations of simulation work, this book links theory, algorithms and implementation procedures, demonstrating the simulation results with graphics that are intuitive without sacrificing academic rigor. Further, it pays due attention to both the conceptual framework and the implementation procedures. The book offers a valuable resource for scientists, researchers and graduate students in the field of Control, Aerospace Technology and Astronautics, especially those interested in artificial intelligence and Unmanned Aerial Vehicles. Professor Haibin Duan and Dr. Pei Li, both work at Beihang University (formerly Beijing University of Aeronautics & Astronautics, BUAA). Prof Duan's academic website is: http://hbduan.buaa.edu.cn

Download or read book Agile Autonomy Learning High Speed Vision Based Flight written by Antonio Loquercio and published by Springer Nature. This book was released on 2023-04-24 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the astonishing potential of deep sensorimotor policies for agile vision-based quadrotor flight. Quadrotors are among the most agile and dynamic machines ever created. However, developing fully autonomous quadrotors that can approach or even outperform the agility of birds or human drone pilots with only onboard sensing and computing is challenging and still unsolved. Deep sensorimotor policies, generally trained in simulation, enable autonomous quadrotors to fly faster and more agile than what was possible before. While humans and birds still have the advantage over drones, the author shows the current research gaps and discusses possible future solutions.

Download or read book Imaging and Sensing for Unmanned Aircraft Systems written by Vania V. Estrela and published by Institution of Engineering and Technology. This book was released on 2020-02-01 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume book set explores how sensors and computer vision technologies are used for the navigation, control, stability, reliability, guidance, fault detection, self-maintenance, strategic re-planning and reconfiguration of unmanned aircraft systems (UAS). Volume 1 concentrates on UAS control and performance methodologies including Computer Vision and Data Storage, Integrated Optical Flow for Detection and Avoidance Systems, Navigation and Intelligence, Modeling and Simulation, Multisensor Data Fusion, Vision in Micro-Aerial Vehicles (MAVs), Computer Vision in UAV using ROS, Security Aspects of UAV and Robot Operating System, Vision in Indoor and Outdoor Drones, Sensors and Computer Vision, and Small UAV for Persistent Surveillance. Volume 2 focuses on UAS deployment and applications including UAV-CPSs as a Testbed for New Technologies and a Primer to Industry 5.0, Human-Machine Interface Design, Open Source Software (OSS) and Hardware (OSH), Image Transmission in MIMO-OSTBC System, Image Database, Communications Requirements, Video Streaming, and Communications Links, Multispectral vs Hyperspectral Imaging, Aerial Imaging and Reconstruction of Infrastructures, Deep Learning as an Alternative to Super Resolution Imaging, and Quality of Experience (QoE) and Quality of Service (QoS).

Download or read book Vision based Emergency Landing of Small Unmanned Aircraft Systems written by Parker Chase Lusk and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents a machine vision-based approach to emergency landing for small unmanned aircraft systems. In the event of an emergency, the vehicle uses a pre-compiled database of potential landing sites to select the most accessible location to land based on vehicle health. Because it is impossible to know the current state of any ground environment, a camera is used for real-time visual feedback. Using the recently developed Recursive-RANSAC algorithm, an arbitrary number of moving ground obstacles can be visually detected and tracked. If obstacles are present in the selected ditch site, the emergency landing system chooses a new ditch site to mitigate risk. This system is called Safe2Ditch.

Download or read book Vision based Emergency Landing of Small Unmanned Aircraft Systems cParker Chase Lusk written by Parker Chase Lusk and published by . This book was released on 2018 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents a machine vision-based approach to emergency landing for small unmanned aircraft systems. In the event of an emergency, the vehicle uses a pre-compiled database of potential landing sites to select the most accessible location to land based on vehicle health. Because it is impossible to know the current state of any ground environment, a camera is used for real-time visual feedback. Using the recently developed Recursive-RANSAC algorithm, an arbitrary number of moving ground obstacles can be visually detected and tracked. If obstacles are present in the selected ditch site, the emergency landing system chooses a new ditch site to mitigate risk. This system is called Safe2Ditch.

Download or read book Unmanned Aircraft Design written by Mohammad Sadraey and published by Morgan & Claypool Publishers. This book was released on 2017-09-19 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides fundamental principles, design procedures, and design tools for unmanned aerial vehicles (UAVs) with three sections focusing on vehicle design, autopilot design, and ground system design. The design of manned aircraft and the design of UAVs have some similarities and some differences. They include the design process, constraints (e.g., g-load, pressurization), and UAV main components (autopilot, ground station, communication, sensors, and payload). A UAV designer must be aware of the latest UAV developments; current technologies; know lessons learned from past failures; and they should appreciate the breadth of UAV design options. The contribution of unmanned aircraft continues to expand every day and over 20 countries are developing and employing UAVs for both military and scientific purposes. A UAV system is much more than a reusable air vehicle or vehicles. UAVs are air vehicles, they fly like airplanes and operate in an airplane environment. They are designed like air vehicles; they have to meet flight critical air vehicle requirements. A designer needs to know how to integrate complex, multi-disciplinary systems, and to understand the environment, the requirements and the design challenges and this book is an excellent overview of the fundamentals from an engineering perspective. This book is meant to meet the needs of newcomers into the world of UAVs. The materials are intended to provide enough information in each area and illustrate how they all play together to support the design of a complete UAV. Therefore, this book can be used both as a reference for engineers entering the field or as a supplementary text for a UAV design course to provide system-level context for each specialized topic.

Download or read book Vision based Automatic Landing of a Rotary UAV written by Iryna Borshchova and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).

Download or read book Position Control of a Quadrotor UAV Using Stereo Computer Vision written by Geordi McGrath and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Quadrotors are a recent popular consumer product, prompting further developments with regards to combining attitude and position control for such unmanned aerial vehicles (UAVs). The quadrotor's attitude (orientation) can be controlled using measurements from small and inexpensive sensors such as gyroscopes, accelerometers, and magnetometers combined in a complementary filter. The quadrotor's position can be controlled using a global positioning system (GPS); this has shown to be an effective method but is not reliable in urban or indoor environments where quadrotors may be flown. An alternative method such as visual servoing may provide reliable position control in urban environments. Visual servoing uses one or more on-board cameras to detect visual features in their field-of-view. If more than one camera is used, a more accurate position can be determined. This work discusses the the application of stereo visual servoing to a quadrotor for position control combined in a Kalman filter with IMU readings to provide a better estimate of its position.

Download or read book Computer Vision in Runway Detection for UAV Approach and Landing written by and published by . This book was released on 2015 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Embedded Platforms for UAS Landing Path and Obstacle Detection written by Umberto Papa and published by Springer. This book was released on 2018-01-05 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on the design and development of a system that assists remote pilots during the landing procedure. In particular, it covers a previously neglected topic, namely the search for the best pathway and landing site. It describes the system’s components, such as the ultrasonic sensor, infrared sensor and optical sensor, in detail, and discusses the experimental tests carried out in both controlled laboratory and real-world environments. Providing a fascinating survey of the state of the art in the field of unmanned aircraft system electronics design and development, the book also presents recent advances in and cutting-edge methodologies for the development of acquisition systems and inexpensive sensor design for navigation data.

Download or read book Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques written by Thusnavis, Bella Mary I. and published by IGI Global. This book was released on 2022-05-27 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned aerial vehicles (UAVs) and artificial intelligence (AI) are gaining the attention of academic and industrial researchers due to the freedoms that UAVs afford when operating and monitoring activities remotely. Applying machine learning and deep learning techniques can result in fast and reliable outputs and have helped in real-time monitoring, data collection and processing, and prediction. UAVs utilizing these techniques can become instrumental tools for computer/wireless networks, smart cities, military applications, agricultural sectors, and mining. Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques is an essential reference source that covers pattern recognition, machine and deep learning-based methods, and other AI techniques and the impact they have when applied to different real-time applications of UAVs. It synthesizes the scope and importance of machine learning and deep learning models in enhancing UAV capabilities, solutions to problems, and numerous application areas. Covering topics such as vehicular surveillance systems, yield prediction, and human activity recognition, this premier reference source is a comprehensive resource for computer scientists; AI engineers; data scientists; agriculturalists; government officials; military leaders; business managers and leaders; students and faculty of higher education; academic libraries; academicians; and researchers in computer science, computer vision, pattern recognition, imaging, and engineering.

Download or read book Advances in Aerial Sensing and Imaging written by Sandeep Kumar and published by John Wiley & Sons. This book was released on 2024-03-06 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Aerial Sensing and Imaging This groundbreaking book is a comprehensive guide to the technology found in the complex field of aerial sensing and imaging, and the real-world challenges that stem from its growing significance and demand. The advent of unmanned aerial vehicles (UAVs), or drones, along with advancements in sensor technology and image processing techniques, has further enhanced the capabilities and applications of aerial sensing and imaging. These developments have opened up new research, innovation, and exploration avenues. Aerial sensing and imaging have rapidly evolved over the past few decades and have revolutionized several fields, including land cover and usage prediction, crop and livestock management, road accident monitoring, poverty estimation, defense, agriculture, forest fire detection, UAV security issues, and open parking management. This book provides a comprehensive understanding and knowledge of the underlying technology and its practical applications in different domains. Audience Computer science and artificial intelligence researchers working in the fields of aerial sensing and imaging, as well as professionals working in industries such as agriculture, geology, surveying, urban planning, disaster response, etc; this book provides them with practical guidance and instruction on how to apply aerial sensing and imaging for various purposes and stay up-to-date with the latest developments in the domain.