Download or read book Obstacle Detection Using Monocular Camera for Low Flying Unmanned Aerial Vehicle written by Fan Zhang and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Obstacle Detection and Avoidance for UAVs in Nap of the Earth Flight written by Roger Fusté Mollà and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A vision-based obstacle detection and avoidance algorithm for Unmanned Aerial Vehicles (UAVs) in fast and low flights ('Nap of the Earth' flights) has been developed. First, a literature review has been performed for both obstacle detection methods and obstacle avoidance methods. Two main categories have been recognised amongst the approaches used for each of them: the use of either a monocular camera or a stereo camera for the obstacle detection; and either reactive or anticipative methods for the obstacle avoidance. The implemented algorithm uses a stereo camera and an anticipative approach, as they have been identified as the most suitable techniques for fast flights. The stereo pairs of images are used to construct a 3D global occupancy map with a novel cell tagging method. This map is then used to calculate a set of waypoints which can lead the vehicle safely towards its goal. Finally, a novel optimisation algorithm is used to compute the fastest feasible polynomial trajectory along this set of waypoints to bring the vehicle to the target in the minimum achievable amount of time.

Download or read book Stereoscopic Imaging for Obstacle Detection Onboard Low flying Unmanned Aerial Vehicles written by Emad Hanna and published by . This book was released on 2010 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advanced Sensing in Image Processing and IoT written by Rashmi Gupta and published by CRC Press. This book was released on 2021-03-26 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides future research directions in IoT and image processing based Energy, Industry, and Healthcare domain and explores the different applications of its associated technologies. However, the Internet of Things and image processing is a very big field with a lot of subfields, which are very important such as Smart Homes to improve our daily life, Smart Cities to improve the citizens' life, Smart Towns to recover the livability and traditions, Smart Earth to protect our world, and Industrial Internet of Things to create safer and easier jobs. This book considers very important research areas in Energy, Industry, and Healthcare domain with IoT and image processing applications.The aim of the book to highlights future directions of optimization methods in various engineering and science applications in various IoT and image processing applications. Emphasis is given to deep learning and similar models of neural network-based learning techniques employed in solving optimization problems of different engineering and science applications. The role of AI in mechatronics is also highlighted using suitable optimization methods. This book considers very important research areas in Energy, Industry, and Healthcare. It addresses major issues and challenges in Energy, Industry, and Healthcare and solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations. Key sailing Features: The impact of the proposed book is to provide a major area of concern to develop a foundation for the implementation process of new image processing and IoT devices based on Energy, Industry, and Healthcare related technology. The researchers working on image processing and IoT devices can correlate their work with other requirements of advanced technology in Energy, Industry, and Healthcare domain. To make aware of the latest technology like AI and Machine learning in Energy, Industry, and Healthcare related technology. Useful for the researcher to explore new things like Security, cryptography, and privacy in Energy, Industry, and Healthcare related technology. People who want to start in Energy, Industry, and Healthcare related technology with image processing and IoT world.

Download or read book Robust Learning of a Depth Map for Obstacle Avoidance with a Monocular Stabilized Flying Camera written by Clément Pinard and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Customer unmanned aerial vehicles (UAVs) are mainly flying cameras. They democratized aerial footage, but with thei success came security concerns.This works aims at improving UAVs security with obstacle avoidance, while keeping a smooth flight. In this context, we use only one stabilized camera, because of weight and cost incentives.For their robustness in computer vision and thei capacity to solve complex tasks, we chose to use convolutional neural networks (CNN). Our strategy is based on incrementally learning tasks with increasing complexity which first steps are to construct a depth map from the stabilized camera. This thesis is focused on studying ability of CNNs to train for this task.In the case of stabilized footage, the depth map is closely linked to optical flow. We thus adapt FlowNet, a CNN known for optical flow, to output directly depth from two stabilized frames. This network is called DepthNet.This experiment succeeded with synthetic footage, but is not robust enough to be used directly on real videos. Consequently, we consider self supervised training with real videos, based on differentiably reproject images. This training method for CNNs being rather novel in literature, a thorough study is needed in order not to depend too moch on heuristics.Finally, we developed a depth fusion algorithm to use DepthNet efficiently on real videos. Multiple frame pairs are fed to DepthNet to get a great depth sensing range.

Download or read book Advances in Guidance Navigation and Control written by Liang Yan and published by Springer Nature. This book was released on 2023-02-10 with total page 7455 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircrafts. It covers a wide range of topics, including but not limited to, intelligent computing communication and control; new methods of navigation, estimation and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation and control of miniature aircraft; and sensor systems for guidance, navigation and control etc. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.

Download or read book Intelligent Autonomy of UAVs written by Yasmina Bestaoui Sebbane and published by CRC Press. This book was released on 2018-03-14 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Autonomy of UAVs: Advanced Missions and Future Use provides an approach to the formulation of the fundamental task typical to any mission and provides guidelines of how this task can be solved by different generic robotic problems. As such, this book aims to provide a systems engineering approach to UAV projects, discovering the real problems that need to be resolved independently of the application. After an introduction to the rapidly evolving field of aerial robotics, the book presents topics such as autonomy, mission analysis, human-UAV teams, homogeneous and heterogeneous UAV teams, and finally, UAV-UGV teams. It then covers generic robotic problems such as orienteering and coverage. The book next introduces deployment, patrolling, and foraging, while the last part of the book tackles an important application: aerial search, tracking, and surveillance. This book is meant for both scientists and practitioners. For practitioners, it presents existing solutions that are categorized according to various missions: surveillance and reconnaissance, 3D mapping, urban monitoring, precision agriculture, forestry, disaster assessment and monitoring, security, industrial plant inspection, etc. For scientists, it provides an overview of generic robotic problems such as coverage and orienteering; deployment, patrolling and foraging; search, tracking, and surveillance. The design and analysis of algorithms raise a unique combination of questions from many fields, including robotics, operational research, control theory, and computer science.

Download or read book Advances in Signal Processing and Intelligent Recognition Systems written by Sabu M. Thampi and published by Springer. This book was released on 2019-01-05 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Symposium on Advances in Signal Processing and Intelligent Recognition Systems, SIRS 2018, held in Bangalore, India, in September 2018. The 28 revised full papers and 11 revised short papers presented were carefully reviewed and selected from 92 submissions. The papers cover wide research fields including information retrieval, human-computer interaction (HCI), information extraction, speech recognition.

Download or read book Omnidirectional Obstacle Detection Using Minimal Sensing written by Audren Damien Prigent Cloitre and published by . This book was released on 2019 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: An integrated approach to visual obstacle detection for aerial multi-rotor vehicles (drones) is introduced. The approach achieves omnidirectional detection of obstacles via suitable synergy of hardware and software. The drone requires a specific arrangement of two cameras, opposing each other, and placed below and above the drone. A total coverage of the drone's surroundings is achieved by fitting each camera with a fisheye lens whose field of view is significantly greater than 180 degrees. The combined field of view of the cameras is omnidirectional, and may be conceptually subdivided into three regions: the monocular portions of each camera (centered at the north and south poles of the drone) and the stereo portion common to both cameras (circling the drone's equator). To use both the stereo and monocular data, a special image projection is developed, based on a model of the world as a 'capsule'. The capsule projection consists in a perspective cylindrical projection in the stereo portion, and a planar projection for the two monocular portions. Fisheye images warped by the capsule projection are called capsule images. A stereo algorithm is applied to the cylindrical portion of the capsule images to produce a stereo point cloud. Image features are tracked on the capsule images, since the projection is continuous across the stereo and monocular portions. The tracked features are used in a structure-from-motion algorithm that estimates their 3D locations, and produces a point cloud representing landmarks. The landmark and stereo point clouds are merged into a single set and projected to the unit sphere centered at the drone's coordinate frame. A 2D spherical Delaunay triangulation algorithm is used to build a triangular mesh from the projected points. The vertices of the mesh are then back-projected to their original 3D location, to create a 3D triangulated surface that represents the obstacles surrounding the drone. The overall method is validated via field experiments conducted with a drone whose design implements our specific camera arrangement. The drone system design is detailed and the experimental results show that this drone can effectively detect obstacles in arbitrary direction, with satisfactory accuracy.

Download or read book Autonomous Monocular Obstacle Detection for Avoidance in Quadrotor UAVs written by Panos Valavanis and published by . This book was released on 2019 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: Obtained results contribute to: i.) a thorough understanding of advantages, disadvan- tages and applicability limitations of using only monocular vision for obstacle detection and avoidance; ii.) real-time applicability, and, iii.) applicability restrictions due to limita- tions of existing support technologies, i.e., ROS, Gazebo and the TUM Simulator package. A major contribution of the developed system is that it may be used as an open-source ed- ucational tool for students, practitioners and end users who are interested in unmanned aviation.

Download or read book Machine Vision Algorithms and Applications written by Carsten Steger and published by John Wiley & Sons. This book was released on 2018-03-12 with total page 533 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this successful machine vision textbook is completely updated, revised and expanded by 35% to reflect the developments of recent years in the fields of image acquisition, machine vision algorithms and applications. The new content includes, but is not limited to, a discussion of new camera and image acquisition interfaces, 3D sensors and technologies, 3D reconstruction, 3D object recognition and state-of-the-art classification algorithms. The authors retain their balanced approach with sufficient coverage of the theory and a strong focus on applications. All examples are based on the latest version of the machine vision software HALCON 13.

Download or read book Embedded Platforms for UAS Landing Path and Obstacle Detection II written by Gennaro Ariante and published by Springer. This book was released on 2024-07-12 with total page 0 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 navigation. It focuses on the design and development of a ground station that assists remote pilots during maneuvers such as take-off or landing procedures, in case a high accuracy is required or the GNSS signal is lost. Continuing the tradition of the previous volume, and being its revised edition, this book covers the latest UAS regulations together with updated strategies for finding the best and safest trajectory and landing site, with a special focus on urban air mobility applications. It describes the system’s components, such as the LiDAR sensor, the temperature and humidity sensors, the Raspberry Pi 3 controller, and the Bluetooth Low Energy Transmitter, in detail. Further, it discusses the experimental tests carried out in both controlled laboratory settings and real-world environments. All in all, this book offers a timely survey of both regulations of and electronics design for unmanned aircraft systems, with extensive information on new methods and technologies for the development of Detect and Avoid systems for unmanned aerial vehicles.

Download or read book Autonomous Navigation and Teleoperation of Unmanned Aerial Vehicles Using Monocular Vision written by Diego Alberto Mercado-Ravell and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present document addresses, theoretically and experimentally, the most relevant topics for Unmanned Aerial Vehicles (UAVs) in autonomous and semi-autonomous navigation. According with the multidisciplinary nature of the studied problems, a wide range of techniques and theories are covered in the fields of robotics, automatic control, computer science, computer vision and embedded systems, among others. As part of this thesis, two different experimental platforms were developed in order to explore and evaluate various theories and techniques of interest for autonomous navigation. The first prototype is a quadrotor specially designed for outdoor applications and was fully developed in our lab. The second testbed is composed by a non expensive commercial quadrotor kind AR. Drone, wireless connected to a ground station equipped with the Robot Operating System (ROS), and specially intended to test computer vision algorithms and automatic control strategies in an easy, fast and safe way. In addition, this work provides a study of data fusion techniques looking to enhance the UAVs pose estimation provided by commonly used sensors. Two strategies are evaluated in particular, an Extended Kalman Filter (EKF) and a Particle Filter (PF). Both estimators are adapted for the system under consideration, taking into account noisy measurements of the UAV position, velocity and orientation. Simulations show the performance of the developed algorithms while adding noise from real GPS (Global Positioning System) measurements. Safe and accurate navigation for either autonomous trajectory tracking or haptic teleoperation of quadrotors is presented as well. A second order Sliding Mode (2-SM) control algorithm is used to track trajectories while avoiding frontal collisions in autonomous flight. The time-scale separation of the translational and rotational dynamics allows us to design position controllers by giving desired references in the roll and pitch angles, which is suitable for quadrotors equipped with an internal attitude controller. The 2-SM control allows adding robustness to the closed-loop system. A Lyapunov based analysis probes the system stability. Vision algorithms are employed to estimate the pose of the vehicle using only a monocular SLAM (Simultaneous Localization and Mapping) fused with inertial measurements. Distance to potential obstacles is detected and computed using the sparse depth map from the vision algorithm. For teleoperation tests, a haptic device is employed to feedback information to the pilot about possible collisions, by exerting opposite forces. The proposed strategies are successfully tested in real-time experiments, using a low-cost commercial quadrotor. Also, conception and development of a Micro Aerial Vehicle (MAV) able to safely interact with human users by following them autonomously, is achieved in the present work. Once a face is detected by means of a Haar cascade classifier, it is tracked applying a Kalman Filter (KF), and an estimation of the relative position with respect to the face is obtained at a high rate. A linear Proportional Derivative (PD) controller regulates the UAV's position in order to keep a constant distance to the face, employing as well the extra available information from the embedded UAV's sensors. Several experiments were carried out through different conditions, showing good performance even under disadvantageous scenarios like outdoor flight, being robust against illumination changes, wind perturbations, image noise and the presence of several faces on the same image. Finally, this thesis deals with the problem of implementing a safe and fast transportation system using an UAV kind quadrotor with a cable suspended load. The objective consists in transporting the load from one place to another, in a fast way and with minimum swing in the cable.

Download or read book Remote Sensing and Actuation Using Unmanned Vehicles written by Haiyang Chao and published by John Wiley & Sons. This book was released on 2012-08-28 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned systems and robotics technologies have become very popular recently owing to their ability to replace human beings in dangerous, tedious, or repetitious jobs. This book fill the gap in the field between research and real-world applications, providing scientists and engineers with essential information on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes. Target scenarios include environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks.

Download or read book Obstacle Detection in a See and avoid System for Unmanned Aerial Vehicles written by and published by . This book was released on 2004 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book On Autonomous Target Tracking for UAVs written by Panagiotis Theodorakopoulos and published by . This book was released on 2009 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most applications of Unmanned Aerial Vehicles are related to events that occur on the ground. In particular, ground target tracking, be the target static, slowly moving or maneuvering at high speeds, is an essential task for UAVs. The overall objective of this thesis is to provide methods to endow a drone to autonomously track a moving ground target, under the following conditions: - A fixed wing UAV equipped with a monocular camera. - Presence of obstacles that hinder ground visibility. - No Fly Zones that limit the airspace. - Restrictions on the field of view of the observing sensor (a camera) - Various target dynamics and behavior: the target may be either moving on an open field or on a road network, and also has dynamic constraints (e.g. if it is a car). It can be neutral or evasive: in the latter case, it can exploit the presence of obstacles, denoted as "shadows" to avoid being tracked by the UAV, making the problem akin to a "hide and seek" game. The thesis proposes three approaches to tackle this problem: - A control based navigation method, - An adversarial predictive method, - And a discrete game theoretic approach. Results obtained in realistic simulations and with an actual UAV are presented to evaluate and compare the pros and cons of each approach. Extensions to the multi-drone case are also considered.

Download or read book Development of Three dimensional Obstacle Sensing for Wildlife Monitoring UAVs Using Complementary Low cost Sensors written by and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation presents a strategy that generates three-dimensional (3D) obstacle sensing views for wildlife monitoring unmanned aerial vehicles (UAVs) by fusing the obstacles range measurements with the corresponding pixel values. To obtain the range measurements, a laser range sensor (Lidar-lite V3) was attached to a pan-tilt platform which enabled angular movements for the 3D perception of spatial surfaces through the generation of 3D point clouds. To obtain the scene projection on a two-dimensional (2D) plane, a camera (Logitech webcam C930e) was mounted on top of the pan-tilt platform to capture the scene images. Through utilizing the camera’s projection matrix, the 3D world points in homogenous form were projected into the corresponding 2D image space to acquire the chrome information before being re-projected to the 3D point clouds. As a result, 3D obstacle sensing views providing the obstacles range and appearances were generated. The developed views were then wirelessly uploaded to a station computer to provide situation awareness to the UAV pilot based on the ground station. The time taken (framerate) to generate one frame of obstacle perception with a resolution of 125 x 250 pixels was 1 second. The developed fusion strategy can be widely used for wildlife monitoring UAVs, and other practical cases where dynamic environment awareness is needed.