Object Tracking in a Computer Vision Based Autonomous See-and-avoid System for Unmanned Aerial Vehicles PDF Download

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 61

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Author: Aleksander Nawrat
Publisher: Springer
ISBN: 9783319003702
Category : Computers
Languages : en
Pages : 344

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Book Description
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.

Author: Gourab Sen Gupta
Publisher: Springer
ISBN: 3642373879
Category : Technology & Engineering
Languages : en
Pages : 342

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There isn’t a facet of human life that has not been touched and influenced by robots and automation. What makes robots and machines versatile is their computational intelligence. While modern intelligent sensors and powerful hardware capabilities have given a huge fillip to the growth of intelligent machines, the progress in the development of algorithms for smart interaction, collaboration and pro-activeness will result in the next quantum jump. This book deals with the recent advancements in design methodologies, algorithms and implementation techniques to incorporate intelligence in robots and automation systems. Several articles deal with navigation, localization and mapping of mobile robots, a problem that engineers and researchers are grappling with all the time. Fuzzy logic, neural networks and neuro-fuzzy based techniques for real world applications have been detailed in a few articles. This edited volume is targeted to present the latest state-of-the-art computational intelligence techniques in Robotics and Automation. It is a compilation of the extended versions of the very best papers selected from the many that were presented at the 5th International Conference on Automation, Robotics and Applications (ICARA 2011) which was held in Wellington, New Zealand from 6-8 December, 2011. Scientists and engineers who work with robots and automation systems will find this book very useful and stimulating.

Author: Teutsch, Michael
Publisher: KIT Scientific Publishing
ISBN: 3731503204
Category : Electronic computers. Computer science
Languages : en
Pages : 242

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Unmanned Aerial Vehicles (UAVs) equipped with video cameras are a flexible support to ensure civil and military safety and security. In this thesis, a video processing chain is presented for moving object detection in aerial video surveillance. A Track-Before-Detect (TBD) algorithm is applied to detect motion that is independent of the camera motion. Novel robust and fast object detection and segmentation approaches improve the baseline TBD and outperform current state-of-the-art methods.

Author: Hani Hunud Abia Kadouf
Publisher:
ISBN:
Category :
Languages : en
Pages : 220

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Useful applications of Unmanned Air Vehicles (UAVs) include aerial surveillance in hostile military zones or search and rescue operations in disaster stricken areas. The increased visual capacity of UAVs also helps support ground vehicles during scouting missions or to extend communication beyond insurmountable land or water barriers. Computer vision techniques provide a simplistic means to convey information for motion control of a UAV. Hence this work focuses on the development of a vision based image processing algorithm for autonomous navigation of a quadrotor UAV. A camera was used to capture an aerial field of view and transmit a video stream of its perspective to a base station- where OpenCV 2.3.1 vision processing software was used to implement a vision processing algorithm. The algorithm comprises of colour thresholding, the use of image moment and blob detection to detect and track an object within the camea view. Experimental readings of an object's displacement at three altitudes; 1.5m, 2.0m and 2.5m were used to derive pixel-to-cm conversion equations based on the target's pixel coordinates on the viewing window. Through a statistical analysis of variance and standard deviation conducted on 15 experimental readings of displacement ranging from 5cm to 25cm; it was shown that the vision system is best suited for tracking displacements at lower altitude flights. Hence, the best result for variance and standard were achieved when using the derived equation and were 0.64 and 0.8 respectively. The equation derived was also used to derive GPS locking coordinates. Pixel coordinates of a target on the camera display were then used to produce GPS locking coordinates for the quadrotor to track a target object.

Author: Pier Luigi Mazzeo
Publisher: BoD – Books on Demand
ISBN: 1789851572
Category : Computers
Languages : en
Pages : 208

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Book Description
Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of-the-art and new algorithms, methods, and systems of these research fields by using deep learning. It is organized into nine chapters across three sections. Section I discusses object detection and tracking ideas and algorithms; Section II examines applications based on re-identification challenges; and Section III presents applications based on FR research.

Author: Plamen Angelov
Publisher: John Wiley & Sons
ISBN: 0470979755
Category : Technology & Engineering
Languages : en
Pages : 381

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Book Description
There is increasing interest in the potential of UAV (Unmanned Aerial Vehicle) and MAV (Micro Air Vehicle) technology and their wide ranging applications including defence missions, reconnaissance and surveillance, border patrol, disaster zone assessment and atmospheric research. High investment levels from the military sector globally is driving research and development and increasing the viability of autonomous platforms as replacements for the remotely piloted vehicles more commonly in use. UAV/UAS pose a number of new challenges, with the autonomy and in particular collision avoidance, detect and avoid, or sense and avoid, as the most challenging one, involving both regulatory and technical issues. Sense and Avoid in UAS: Research and Applications covers the problem of detect, sense and avoid in UAS (Unmanned Aircraft Systems) in depth and combines the theoretical and application results by leading academics and researchers from industry and academia. Key features: Presents a holistic view of the sense and avoid problem in the wider application of autonomous systems Includes information on human factors, regulatory issues and navigation, control, aerodynamics and physics aspects of the sense and avoid problem in UAS Provides professional, scientific and reliable content that is easy to understand, and Includes contributions from leading engineers and researchers in the field Sense and Avoid in UAS: Research and Applications is an invaluable source of original and specialised information. It acts as a reference manual for practising engineers and advanced theoretical researchers and also forms a useful resource for younger engineers and postgraduate students. With its credible sources and thorough review process, Sense and Avoid in UAS: Research and Applications provides a reliable source of information in an area that is fast expanding but scarcely covered.

Author: G. Rajakumar
Publisher: Springer Nature
ISBN: 9819917670
Category : Technology & Engineering
Languages : en
Pages : 923

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The book is a collection of high-quality research papers presented at Intelligent Communication Technologies and Virtual Mobile Networks (ICICV 2023), held at Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India, during February 16–17, 2023. The book shares knowledge and results in theory, methodology, and applications of communication technology and mobile networks. The book covers innovative and cutting-edge work of researchers, developers, and practitioners from academia and industry working in the area of computer networks, network protocols and wireless networks, data communication technologies, and network security.

Author: Benjamin Kiefer
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
The integration of computer vision technology into Unmanned Aerial Vehicles (UAVs) has become increasingly crucial in various aerial vision-based applications. Despite the great significant success of generic computer vision methods, a considerable performance drop is observed when applied to the UAV domain. This is due to large variations in imaging conditions, such as varying altitudes, dynamically changing viewing angles, and varying capture times resulting in vast changes in lighting conditions. Furthermore, the need for real-time algorithms and the hardware constraints pose specific problems that require special attention in the development of computer vision algorithms for UAVs. In this dissertation, we demonstrate that domain knowledge in the form of meta data is a valuable source of information and thus propose domain-aware computer vision methods by using freely accessible sensor data. The pipeline for computer vision systems on UAVs is discussed, from data mission planning, data acquisition, labeling and curation, to the construction of publicly available benchmarks and leaderboards and the establishment of a wide range of baseline algorithms. Throughout, the focus is on a holistic view of the problems and opportunities in UAV-based computer vision, and the aim is to bridge the gap between purely software-based computer vision algorithms and environmentally aware robotic platforms. The results demonstrate that incorporating meta data obtained from onboard sensors, such as GPS, barometers, and inertial measurement units, can significantly improve the robustness and interpretability of computer vision models in the UAV domain. This leads to more trustworthy models that can overcome challenges such as domain bias, altitude variance, synthetic data inefficiency, and enhance perception through environmental awareness in temporal scenarios, such as video object detection, tracking and video anomaly detection. The proposed methods and benchmarks provide a foundation for future research in this area, and the results suggest promising directions for developing environmentally aware robotic platforms. Overall, this work highlights the potential of combining computer vision and robotics to tackle real-world challenges and opens up new avenues for interdisciplinary research.

Author: Diego Alberto Mercado-Ravell
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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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.