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EBookClubs

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Book Monocular Vision based Obstacle Detection for Unmanned Systems

Download or read book Monocular Vision based Obstacle Detection for Unmanned Systems written by Carlos Wang and published by . This book was released on 2011 with total page 97 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many potential indoor applications exist for autonomous vehicles, such as automated surveillance, inspection, and document delivery. A key requirement for autonomous operation is for the vehicles to be able to detect and map obstacles in order to avoid collisions. This work develops a comprehensive 3D scene reconstruction algorithm based on known vehicle motion and vision data that is specifically tailored to the indoor environment. Visible light cameras are one of the many sensors available for capturing information from the environment, and their key advantages over other sensors are that they are light weight, power efficient, cost effective, and provide abundant information about the scene. The emphasis on 3D indoor mapping enables the assumption that a large majority of the area to be mapped is comprised of planar surfaces such as floors, walls and ceilings, which can be exploited to simplify the complex task of dense reconstruction of the environment from monocular vision data. In this thesis, the Planar Surface Reconstruction (PSR) algorithm is presented. It extracts surface information from images and combines it with 3D point estimates in order to generate a reliable and complete environment map. It was designed to be used for single cameras with the primary assumption that the objects in the environment are flat, static and chromatically unique. The algorithm finds and tracks Scale Invariant Feature Transform (SIFT) features from a sequence of images to calculate 3D point estimates. The individual surface information is extracted using a combination of the Kuwahara filter and mean shift segmentation, which is then coupled with the 3D point estimates to fit these surfaces in the environment map. The resultant map consists of both surfaces and points that are assumed to represent obstacles in the scene. A ground vehicle platform was developed for the real-time implementation of the algorithm and experiments were done to assess the PSR algorithm. Both clean and cluttered scenarios were used to evaluate the quality of the surfaces generated from the algorithm. The clean scenario satisfies the primary assumptions underlying the PSR algorithm, and as a result produced accurate surface details of the scene, while the cluttered scenario generated lower quality, but still promising, results. The significance behind these findings is that it is shown that incorporating object surface recognition into dense 3D reconstruction can significantly improve the overall quality of the environment map.

Book Autonomous Monocular Obstacle Detection for Avoidance in Quadrotor UAVs

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.

Book Obstacle Detection and Avoidance for UAVs in  Nap of the Earth  Flight

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.

Book Deep Learning for Unmanned Systems

Download or read book Deep Learning for Unmanned Systems written by Anis Koubaa and published by Springer Nature. This book was released on 2021-10-01 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is used at the graduate or advanced undergraduate level and many others. Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future. These applications include, but are not limited to, surveillance, search and rescue, environment monitoring, infrastructure monitoring, self-driving cars, contactless last-mile delivery vehicles, autonomous ships, precision agriculture and transmission line inspection to name just a few. These vehicles will benefit from advances of deep learning as a subfield of machine learning able to endow these vehicles with different capability such as perception, situation awareness, planning and intelligent control. Deep learning models also have the ability to generate actionable insights into the complex structures of large data sets. In recent years, deep learning research has received an increasing amount of attention from researchers in academia, government laboratories and industry. These research activities have borne some fruit in tackling some of the challenging problems of manned and unmanned ground, aerial and marine vehicles that are still open. Moreover, deep learning methods have been recently actively developed in other areas of machine learning, including reinforcement training and transfer/meta-learning, whereas standard, deep learning methods such as recent neural network (RNN) and coevolutionary neural networks (CNN). The book is primarily meant for researchers from academia and industry, who are working on in the research areas such as engineering, control engineering, robotics, mechatronics, biomedical engineering, mechanical engineering and computer science. The book chapters deal with the recent research problems in the areas of reinforcement learning-based control of UAVs and deep learning for unmanned aerial systems (UAS) The book chapters present various techniques of deep learning for robotic applications. The book chapters contain a good literature survey with a long list of references. The book chapters are well written with a good exposition of the research problem, methodology, block diagrams and mathematical techniques. The book chapters are lucidly illustrated with numerical examples and simulations. The book chapters discuss details of applications and future research areas.

Book Stochastically Optimized Monocular Vision based Navigation and Guidance

Download or read book Stochastically Optimized Monocular Vision based Navigation and Guidance written by Yoko Watanabe and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this thesis is to design a relative navigation and guidance system for unmanned aerial vehicles (UAVs) for vision-based control applications. The vision-based navigation, guidance and control has been one of the most focused on research topics for the automation of UAVs. This is because in nature, birds and insects use vision as the exclusive sensor for object detection and navigation. In particular, this thesis studies the monocular vision-based navigation and guidance. Since 2-D vision-based measurements are nonlinear with respect to the 3-D relative states, an extended Kalman filter (EKF) is applied in the navigation system design. The EKF-based navigation system is integrated with a real-time image processing algorithm and is tested in simulations and flight tests. The first closed-loop vision-based formation flight has been achieved. In addition, vision-based 3-D terrain recovery was performed in simulations. A vision-based obstacle avoidance problem is specially addressed in this thesis. A navigation and guidance system is designed for a UAV to achieve a mission of waypoint tracking while avoiding unforeseen stationary obstacles by using vision information. A 3-D collision criterion is established by using a collision-cone approach. A minimum-effort guidance (MEG) law is applied for a guidance design, and it is shown that the control effort can be reduced by using the MEG-based guidance instead of a conventional guidance law. The system is evaluated in a 6 DoF flight simulation and also in a flight test. For monocular vision-based control problems, vision-based estimation performance highly depends on the relative motion of the vehicle with respect to the target. Therefore, this thesis aims to derive an optimal guidance law to achieve a given mission under the condition of using the EKF-based relative navigation. Stochastic optimization is formulated to minimize the expected cost including the guidance error and the control effort. A suboptimal guidance law is derived based on an idea of the one-step-ahead (OSA) optimization. Simulation results show that the suggested guidance law significantly improves the guidance performance. Furthermore, the OSA optimization is generalized as the n-step-ahead optimization for an arbitrary number of n, and their optimality and computational cost are investigated.

Book Bio inspired Information and Communication Technologies

Download or read book Bio inspired Information and Communication Technologies written by Yifan Chen and published by Springer Nature. This book was released on 2020-08-10 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed conference proceedings of the 12th International Conference on Bio-inspired Information and Communications Technologies, held in Shanghai, China, in July 2020. Due to the safety concerns and travel restrictions caused by COVID-19, BICT 2020 took place online in a live stream. BICT 2020 aims to provide a world-leading and multidisciplinary venue for researchers and practitioners in diverse disciplines that seek the understanding of key principles, processes and mechanisms in biological systems and leverage those understandings to develop novel information and communications technologies (ICT). The 20 full and 8 short papers were carefully revied and selected from 56 submissions. In addition to the main track targeting broad and mainstream research topics, BICT 2020 includes four special tracks with focused research topics on internet of everything, intelligent internet of things and network applications, intelligent sensor network, and data-driven intelligent modeling, application and optimization.

Book UAV   Based Remote Sensing Volume 1

Download or read book UAV Based Remote Sensing Volume 1 written by Felipe Gonzalez Toro and published by MDPI. This book was released on 2018-04-27 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "UAV-Based Remote Sensing" that was published in Sensors

Book Proceedings of the International Conference on Artificial Intelligence and Computer Vision  AICV2020

Download or read book Proceedings of the International Conference on Artificial Intelligence and Computer Vision AICV2020 written by Aboul-Ella Hassanien and published by Springer Nature. This book was released on 2020-03-23 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 1st International Conference on Artificial Intelligence and Computer Visions (AICV 2020), which took place in Cairo, Egypt, from April 8 to 10, 2020. This international conference, which highlighted essential research and developments in the fields of artificial intelligence and computer visions, was organized by the Scientific Research Group in Egypt (SRGE). The book is divided into sections, covering the following topics: swarm-based optimization mining and data analysis, deep learning and applications, machine learning and applications, image processing and computer vision, intelligent systems and applications, and intelligent networks.

Book Quad Rotorcraft Control

Download or read book Quad Rotorcraft Control written by Luis Rodolfo García Carrillo and published by Springer Science & Business Media. This book was released on 2012-08-12 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quad Rotorcraft Control develops original control methods for the navigation and hovering flight of an autonomous mini-quad-rotor robotic helicopter. These methods use an imaging system and a combination of inertial and altitude sensors to localize and guide the movement of the unmanned aerial vehicle relative to its immediate environment. The history, classification and applications of UAVs are introduced, followed by a description of modelling techniques for quad-rotors and the experimental platform itself. A control strategy for the improvement of attitude stabilization in quad-rotors is then proposed and tested in real-time experiments. The strategy, based on the use low-cost components and with experimentally-established robustness, avoids drift in the UAV’s angular position by the addition of an internal control loop to each electronic speed controller ensuring that, during hovering flight, all four motors turn at almost the same speed. The quad-rotor’s Euler angles being very close to the origin, other sensors like GPS or image-sensing equipment can be incorporated to perform autonomous positioning or trajectory-tracking tasks. Two vision-based strategies, each designed to deal with a specific kind of mission, are introduced and separately tested. The first stabilizes the quad-rotor over a landing pad on the ground; it extracts the 3-dimensional position using homography estimation and derives translational velocity by optical flow calculation. The second combines colour-extraction and line-detection algorithms to control the quad-rotor’s 3-dimensional position and achieves forward velocity regulation during a road-following task. In order to estimate the translational-dynamical characteristics of the quad-rotor (relative position and translational velocity) as they evolve within a building or other unstructured, GPS-deprived environment, imaging, inertial and altitude sensors are combined in a state observer. The text give the reader a current view of the problems encountered in UAV control, specifically those relating to quad-rotor flying machines and it will interest researchers and graduate students working in that field. The vision-based control strategies presented help the reader to a better understanding of how an imaging system can be used to obtain the information required for performance of the hovering and navigation tasks ubiquitous in rotored UAV operation.

Book RiTA 2020

Download or read book RiTA 2020 written by Esyin Chew and published by Springer Nature. This book was released on 2021-09-05 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the Proceedings of the 8th International Conference on Robot Intelligence Technology and Applications (RITA 2020). The areas covered include: Instrumentation and Control, Automation, Autonomous Systems, Biomechatronics and Rehabilitation Engineering, Intelligent Systems, Machine Learning, Mobile Robotics, Social Robotics and Humanoid Robotics, Sensors and Actuators, and Machine Vision, as well as Signal and Image Processing. As a valuable asset, the book offers researchers and practitioners a timely overview of the latest advances in robot intelligence technology and its applications.

Book Advances in Signal Processing and Intelligent Recognition Systems

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.

Book Machine Intelligence and Emerging Technologies

Download or read book Machine Intelligence and Emerging Technologies written by Md. Shahriare Satu and published by Springer Nature. This book was released on 2023-06-10 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNICST 490 and 491 constitutes the proceedings of the First International Conference on Machine Intelligence and Emerging Technologies, MIET 2022, hosted by Noakhali Science and Technology University, Noakhali, Bangladesh, during September 23–25, 2022. The 104 papers presented in the proceedings were carefully reviewed and selected from 272 submissions. This book focuses on theoretical, practical, state-of-art applications, and research challenges in the field of artificial intelligence and emerging technologies. It will be helpful for active researchers and practitioners in this field. These papers are organized in the following topical sections: imaging for disease detection; pattern recognition and natural language processing; bio signals and recommendation systems for wellbeing; network, security and nanotechnology; and emerging technologies for society and industry.

Book Obstacle Detection Using Monocular Camera for Low Flying Unmanned Aerial Vehicle

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:

Book Statistical Process Monitoring Using Advanced Data Driven and Deep Learning Approaches

Download or read book Statistical Process Monitoring Using Advanced Data Driven and Deep Learning Approaches written by Fouzi Harrou and published by Elsevier. This book was released on 2020-07-03 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. - Uses a data-driven based approach to fault detection and attribution - Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems - Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods - Includes case studies and comparison of different methods

Book Advances in Intelligent Information Hiding and Multimedia Signal Processing

Download or read book Advances in Intelligent Information Hiding and Multimedia Signal Processing written by Jeng-Shyang Pan and published by Springer Nature. This book was released on 2021-04-17 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected papers from the Sixteenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, in conjunction with the Thirteenth International Conference on Frontiers of Information Technology, Applications and Tools, held on November 5–7, 2020, in Ho Chi Minh City, Vietnam. It is divided into two volumes and discusses the latest research outcomes in the field of Information Technology (IT) including information hiding, multimedia signal processing, big data, data mining, bioinformatics, database, industrial and Internet of things, and their applications.

Book Proceedings of the 2023 International Conference on Image  Algorithms and Artificial Intelligence  ICIAAI 2023

Download or read book Proceedings of the 2023 International Conference on Image Algorithms and Artificial Intelligence ICIAAI 2023 written by Pushpendu Kar and published by Springer Nature. This book was released on 2023-11-25 with total page 1077 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an open access book. Scope of Conference 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI2023), which will be held from August 11 to August 13 in Singapore provides a forum for researchers and experts in different but related fields to discuss research findings. The scope of ICIAAI 2023 covers research areas such as imaging, algorithms and artificial intelligence. Related fields of research include computer software, programming languages, software engineering, computer science applications, artificial intelligence, Intelligent data analysis, deep learning, high-performance computing, signal processing, information systems, computer graphics, computer-aided design, Computer vision, etc. The objectives of the conference are: The conference aims to provide a platform for experts, scholars, engineers and technicians engaged in the research of image, algorithm and artificial intelligence to share scientific research results and cutting-edge technologies. The conference will discuss the academic trends and development trends of the related research fields of image, algorithm and artificial intelligence together, carry out discussions on current hot issues, and broaden research ideas. It will be a perfect gathering to strengthen academic research and discussion, promote the development and progress of relevant research and application, and promote the development of disciplines and promote talent training.

Book The DelFly

Download or read book The DelFly written by G.C.H.E. de Croon and published by Springer. This book was released on 2015-11-26 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the topics most relevant to autonomously flying flapping wing robots: flapping-wing design, aerodynamics, and artificial intelligence. Readers can explore these topics in the context of the "Delfly", a flapping wing robot designed at Delft University in The Netherlands. How are tiny fruit flies able to lift their weight, avoid obstacles and predators, and find food or shelter? The first step in emulating this is the creation of a micro flapping wing robot that flies by itself. The challenges are considerable: the design and aerodynamics of flapping wings are still active areas of scientific research, whilst artificial intelligence is subject to extreme limitations deriving from the few sensors and minimal processing onboard. This book conveys the essential insights that lie behind success such as the DelFly Micro and the DelFly Explorer. The DelFly Micro, with its 3.07 grams and 10 cm wing span, is still the smallest flapping wing MAV in the world carrying a camera, whilst the DelFly Explorer is the world's first flapping wing MAV that is able to fly completely autonomously in unknown environments. The DelFly project started in 2005 and ever since has served as inspiration, not only to many scientific flapping wing studies, but also the design of flapping wing toys. The combination of introductions to relevant fields, practical insights and scientific experiments from the DelFly project make this book a must-read for all flapping wing enthusiasts, be they students, researchers, or engineers.