Download Free Wireless Communication Networks Supported By Autonomous Uavs And Mobile Ground Robots Book in PDF and EPUB Free Download. You can read online Wireless Communication Networks Supported By Autonomous Uavs And Mobile Ground Robots and write the review.

Wireless Communication Networks Supported by Autonomous UAVs and Mobile Ground Robots covers wireless sensor networks and cellular networks. For wireless sensor networks, the book presents approaches using mobile robots or UAVs to collect sensory data from sensor nodes. For cellular networks, it discusses the approaches to using UAVs to work as aerial base stations to serve cellular users. In addition, the book covers the challenges involved in these two networks, existing approaches (e.g., how to use the public transportation vehicles to play the role of mobile sinks to collect sensory data from sensor nodes), and potential methods to address open questions. - Gives a comprehensive understanding of the development of mobile robot-supported wireless communication approaches - Provides the latest approaches of mobile robot-supported wireless communication, including scheduling approaches with multiple robots and the online and reactive navigation algorithm - Covers interesting research scenarios that include the system model, problem statement, solution and results so that readers will be able to design their own system - Presents unresolved research issues and future research directions
Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery Authoritative resource offering coverage of communication, surveillance, and delivery problems for teams of unmanned aerial vehicles (UAVs) Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery studies various elements of deployment of networks of unmanned aerial vehicle (UAV) base stations for providing communication to ground users in disaster areas, covering problems like ground traffic monitoring, surveillance of environmental disaster areas (e.g. brush fires), using UAVs in rescue missions, converting UAV video surveillance, and more. The work combines practical problems, implementable and computationally efficient algorithms to solve these problems, and mathematically rigorous proofs of each algorithm’s convergence and performance. One such example provided by the authors is a novel biologically inspired motion camouflage algorithm to covert video surveillance of moving targets by an unmanned aerial vehicle (UAV). All autonomous navigation and deployment algorithms developed in the book are computationally efficient, easily implementable in engineering practice, and based only on limited information on other UAVs of each and the environment. Sample topics discussed in the work include: Deployment of UAV base stations for communication, especially with regards to maximizing coverage and minimizing interference Deployment of UAVs for surveillance of ground areas and targets, including surveillance of both flat and uneven areas Navigation of UAVs for surveillance of moving areas and targets, including disaster areas and ground traffic monitoring Autonomous UAV navigation for covert video surveillance, offering extensive coverage of optimization-based navigation Integration of UAVs and public transportation vehicles for parcel delivery, covering both one-way and round trips Professionals in navigation and deployment of unmanned aerial vehicles, along with researchers, engineers, scientists in intersecting fields, can use Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery to gain general knowledge on the subject along with practical, precise, and proven algorithms that can be deployed in a myriad of practical situations.
This book is a printed edition of the Special Issue "UAV-Based Remote Sensing" that was published in Sensors
This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.
This book is the second volume on Cooperative Robots and Sensor Networks. The primary objective of this book is to provide an up-to-date reference for cutting-edge studies and research trends related to mobile robots and wireless sensor networks, and in particular for the coupling between them. Indeed, mobile robots and wireless sensor networks have enabled great potentials and a large space for ubiquitous and pervasive applications. Robotics and wireless sensor networks have mostly been considered as separate research fields and little work has investigated the marriage between these two technologies. However, these two technologies share several features, enable common cyber-physical applications and provide complementary support to each other. The book consists of ten chapters, organized into four parts. The first part of the book presents three chapters related to localization of mobile robots using wireless sensor networks. Two chapters presented new solutions based Extended Kalman Filter and Particle Filter for localizing the robots using range measurements with the sensor network. The third chapter presents a survey on mobility-assisted localization techniques in wireless sensor networks. The second part of the book deals with cooperative robots and sensor networks applications. One chapter presents a comprehensive overview of major applications coupling between robots and sensor networks and provides real-world examples of their cooperation. Two other chapters present applications for underwater robots and sensor networks.
In recent times, remarkable progress has taken place in the field of autonomous vehicles, reshaping industries such as logistics, transportation, defense, and more. The quest for achieving fully autonomous systems has been a thrilling yet demanding journey, as researchers and engineers continually push the limits of technological ingenuity. Autonomous Vehicles - Applications and Perspectives delves into the field of autonomous vehicles across eight chapters that cover various facets of this domain. The book is organized into four sections: "Introduction", "Autonomous Vehicles Enabling Technologies", "Autonomous Vehicles Applications and Potentials", and "Challenges and Perspectives". Its main goal is to provide an informative resource for those interested in autonomous vehicles, inspiring progress and discussions for researchers, students, and professionals alike.
The development of intelligent transportation systems, especially autonomous underwater vehicles, has become significant in marine engineering, with an aim to enhance energy efficiency management and communication systems. This book covers different aspects of optimization of autonomous underwater vehicles and their propulsion systems via machine learning techniques. It further analyses hydrodynamic characteristics including the study of experimental investigation combined with hydrodynamic characteristics backed by MATLAB® codes and simulation study results. Features: Covers utilization of machine learning techniques with a focus on marine science and ocean engineering. Details effect of the intelligent transportation system (ITS) into the sustainable environment and ecology system. Evaluates performance of particle swarm intelligence-based optimization techniques. Reviews propulsion performance of the remote-controlled vehicles based on machine learning techniques. Includes MATLAB® examples and simulation study results. This book is aimed at graduate students and researchers in marine engineering and technology, computer science, and control system engineering.
The volume set LNAI 11740 until LNAI 11745 constitutes the proceedings of the 12th International Conference on Intelligent Robotics and Applications, ICIRA 2019, held in Shenyang, China, in August 2019. The total of 378 full and 25 short papers presented in these proceedings was carefully reviewed and selected from 522 submissions. The papers are organized in topical sections as follows: Part I: collective and social robots; human biomechanics and human-centered robotics; robotics for cell manipulation and characterization; field robots; compliant mechanisms; robotic grasping and manipulation with incomplete information and strong disturbance; human-centered robotics; development of high-performance joint drive for robots; modular robots and other mechatronic systems; compliant manipulation learning and control for lightweight robot. Part II: power-assisted system and control; bio-inspired wall climbing robot; underwater acoustic and optical signal processing for environmental cognition; piezoelectric actuators and micro-nano manipulations; robot vision and scene understanding; visual and motional learning in robotics; signal processing and underwater bionic robots; soft locomotion robot; teleoperation robot; autonomous control of unmanned aircraft systems. Part III: marine bio-inspired robotics and soft robotics: materials, mechanisms, modelling, and control; robot intelligence technologies and system integration; continuum mechanisms and robots; unmanned underwater vehicles; intelligent robots for environment detection or fine manipulation; parallel robotics; human-robot collaboration; swarm intelligence and multi-robot cooperation; adaptive and learning control system; wearable and assistive devices and robots for healthcare; nonlinear systems and control. Part IV: swarm intelligence unmanned system; computational intelligence inspired robot navigation and SLAM; fuzzy modelling for automation, control, and robotics; development of ultra-thin-film, flexible sensors, and tactile sensation; robotic technology for deep space exploration; wearable sensing based limb motor function rehabilitation; pattern recognition and machine learning; navigation/localization. Part V: robot legged locomotion; advanced measurement and machine vision system; man-machine interactions; fault detection, testing and diagnosis; estimation and identification; mobile robots and intelligent autonomous systems; robotic vision, recognition and reconstruction; robot mechanism and design. Part VI: robot motion analysis and planning; robot design, development and control; medical robot; robot intelligence, learning and linguistics; motion control; computer integrated manufacturing; robot cooperation; virtual and augmented reality; education in mechatronics engineering; robotic drilling and sampling technology; automotive systems; mechatronics in energy systems; human-robot interaction.
This book constitutes the proceedings of the 8th International Workshop on Communication Technologies for Vehicles, Nets4Cars/Nets4Trains/Nets4Aircraft 2015, held in Sousse, Tunisia, in May 2015. The 20 papers presented in this volume were carefully reviewed and selected from 27 submissions. The contributions are organized in topical sections named: road; rail; and air.
Explore foundational and advanced issues in UAV cellular communications with this cutting-edge and timely new resource UAV Communications for 5G and Beyond delivers a comprehensive overview of the potential applications, networking architectures, research findings, enabling technologies, experimental measurement results, and industry standardizations for UAV communications in cellular systems. The book covers both existing LTE infrastructure, as well as future 5G-and-beyond systems. UAV Communications covers a range of topics that will be of interest to students and professionals alike. Issues of UAV detection and identification are discussed, as is the positioning of autonomous aerial vehicles. More fundamental subjects, like the necessary tradeoffs involved in UAV communication are examined in detail. The distinguished editors offer readers an opportunity to improve their ability to plan and design for the near-future, explosive growth in the number of UAVs, as well as the correspondingly demanding systems that come with them. Readers will learn about a wide variety of timely and practical UAV topics, like: Performance measurement for aerial vehicles over cellular networks, particularly with respect to existing LTE performance Inter-cell interference coordination with drones Massive multiple-input and multiple-output (MIMO) for Cellular UAV communications, including beamforming, null-steering, and the performance of forward-link C&C channels 3GPP standardization for cellular-supported UAVs, including UAV traffic requirements, channel modeling, and interference challenges Trajectory optimization for UAV communications Perfect for professional engineers and researchers working in the field of unmanned aerial vehicles, UAV Communications for 5G and Beyond also belongs on the bookshelves of students in masters and PhD programs studying the integration of UAVs into cellular communication systems.