Deep Learning for Unmanned Systems

Deep Learning for Unmanned Systems

The book chapters discuss details of applications and future research areas. This book is used at the graduate or advanced undergraduate level and many others.

Author: Anis Koubaa

Publisher: Springer Nature

ISBN: 9783030779399

Category: Technology & Engineering

Page: 732

View: 770

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.
Categories: Technology & Engineering

Proceedings of 2021 International Conference on Autonomous Unmanned Systems ICAUS 2021

Proceedings of 2021 International Conference on Autonomous Unmanned Systems  ICAUS 2021

In: 2019 IEEE International Conference on Unmanned Systems (ICUS), pp. 909–913. IEEE (2019) 36. Chen, Y., Zhang, J., Yang, Q., et al.: Design and verification of UAV maneuver decision simulation system based on deep q-learning network.

Author: Meiping Wu

Publisher: Springer Nature

ISBN: 9789811694929

Category: Artificial intelligence

Page: 3575

View: 388

This book includes original, peer-reviewed research papers from the ICAUS 2021, which offers a unique and interesting platform for scientists, engineers and practitioners throughout the world to present and share their most recent research and innovative ideas. The aim of the ICAUS 2021 is to stimulate researchers active in the areas pertinent to intelligent unmanned systems. The topics covered include but are not limited to Unmanned Aerial/Ground/Surface/Underwater Systems, Robotic, Autonomous Control/Navigation and Positioning/ Architecture, Energy and Task Planning and Effectiveness Evaluation Technologies, Artificial Intelligence Algorithm/Bionic Technology and Its Application in Unmanned Systems. The papers showcased here share the latest findings on Unmanned Systems, Robotics, Automation, Intelligent Systems, Control Systems, Integrated Networks, Modeling and Simulation. It makes the book a valuable asset for researchers, engineers, and university students alike.
Categories: Artificial intelligence

Intelligent Autonomous Drones with Cognitive Deep Learning

Intelligent Autonomous Drones with Cognitive Deep Learning

What is an artificial intelligence (AI)-enabled drone and what can it do? Are AI-enabled drones better than human-controlled drones? This book will answer these questions and more, and empower you to develop your own AI-enabled drone.

Author: David Allen Blubaugh

Publisher: Apress

ISBN: 1484268024

Category: Computers

Page: 0

View: 602

What is an artificial intelligence (AI)-enabled drone and what can it do? Are AI-enabled drones better than human-controlled drones? This book will answer these questions and more, and empower you to develop your own AI-enabled drone. You'll progress from a list of specifications and requirements, in small and iterative steps, which will then lead to the development of Unified Modeling Language (UML) diagrams based in part to the standards established by for the Robotic Operating System (ROS). The ROS architecture has been used to develop land-based drones. This will serve as a reference model for the software architecture of unmanned systems. Using this approach you'll be able to develop a fully autonomous drone that incorporates object-oriented design and cognitive deep learning systems that adapts to multiple simulation environments. These multiple simulation environments will also allow you to further build public trust in the safety of artificial intelligence within drones and small UAS. Ultimately, you'll be able to build a complex system using the standards developed, and create other intelligent systems of similar complexity and capability. Intelligent Autonomous Drones with Cognitive Deep Learning uniquely addresses both deep learning and cognitive deep learning for developing near autonomous drones. What You’ll Learn Examine the necessary specifications and requirements for AI enabled drones for near-real time and near fully autonomous drones Look at software and hardware requirements Understand unified modeling language (UML) and real-time UML for design Study deep learning neural networks for pattern recognition Review geo-spatial Information for the development of detailed mission planning within these hostile environments Who This Book Is For Primarily for engineers, computer science graduate students, or even a skilled hobbyist. The target readers have the willingness to learn and extend the topic of intelligent autonomous drones. They should have a willingness to explore exciting engineering projects that are limited only by their imagination. As far as the technical requirements are concerned, they must have an intermediate understanding of object-oriented programming and design.
Categories: Computers

Advances in Human Factors in Robots and Unmanned Systems

Advances in Human Factors in Robots and Unmanned Systems

Statistical NLP uses machine learning algorithms, such as neural nets or Hidden Markov Models, to allow systems to develop their own rules from correctly tagged and identified human language [6]. Without imposing rules from the outside, ...

Author: Jessie Chen

Publisher: Springer

ISBN: 9783319603841

Category: Technology & Engineering

Page: 358

View: 753

This book focuses on the importance of human factors in the development of safe and reliable unmanned systems. It discusses current challenges such as how to improve the perceptual and cognitive abilities of robots, develop suitable synthetic vision systems, cope with degraded reliability in unmanned systems, predict robotic behavior in case of a loss of communication, the vision for future soldier-robot teams, human-agent teaming, real-world implications for human-robot interaction, and approaches to standardize both the display and control of technologies across unmanned systems. Based on the AHFE 2017 International Conference on Human Factors in Robots and Unmanned Systems, held on July 17–21 in Los Angeles, California, USA, this book is expected to foster new discussion and stimulate new advances in the development of more reliable, safer, and highly functional devices for carrying out automated and concurrent tasks.
Categories: Technology & Engineering

Advances in Human Factors in Robots Drones and Unmanned Systems

Advances in Human Factors in Robots  Drones and Unmanned Systems

Proceedings of the AHFE 2020 Virtual Conference on Human Factors in Robots, Drones and Unmanned Systems, ... and facial recognition system 2.2 Human Body Detection Based on the experiments, deep learning-based approaches perform ...

Author: Matteo Zallio

Publisher: Springer Nature

ISBN: 9783030517588

Category: Technology & Engineering

Page: 122

View: 412

This book focuses on the importance of human factors in the development of safe and reliable robotic and unmanned systems. It discusses current challenges, such as how to improve the perceptual and cognitive abilities of robots, develop suitable synthetic vision systems, cope with degraded reliability in unmanned systems, and predict robotic behavior in relation to human activities. Further, it highlights potential future human-robot and human-agent collaboration, suggesting real-world implications of and approaches for improving human-machine interaction across unmanned systems. Based on the AHFE 2020 Virtual Conference on Human Factors in Robots, Drones and Unmanned Systems, held on July 16–20, 2020, this book is intended to foster discussion and collaborations among researchers and practitioners, thus stimulating new solutions for the development of reliable and safe, human-centered, highly functional devices to perform automated and concurrent tasks.
Categories: Technology & Engineering

Applications of Small Unmanned Aircraft Systems

Applications of Small Unmanned Aircraft Systems

Machine Learning, 20, 273–297. Deng, L., & Yu, D. (2014). Deep learning: Methods and applications. Foundations and Trends in Signal Processing, 7, 197–387. Draˇguţ, L., Tiede, D., & Levick, S.R. (2010). ESP: A tool to estimate scale ...

Author: J.B. Sharma

Publisher: CRC Press

ISBN: 9780429534324

Category: Science

Page: 281

View: 633

Advances in high spatial resolution mapping capabilities and the new rules established by the Federal Aviation Administration in the United States for the operation of Small Unmanned Aircraft Systems (sUAS) have provided new opportunities to acquire aerial data at a lower cost and more safely versus other methods. A similar opening of the skies for sUAS applications is being allowed in countries across the world. Also, sUAS can access hazardous or inaccessible areas during disaster events and provide rapid response when needed. Applications of Small Unmanned Aircraft systems: Best Practices and Case Studies is the first book that brings together the best practices of sUAS applied to a broad range of issues in high spatial resolution mapping projects. Very few sUAS pilots have the knowledge of how the collected imagery is processed into value added mapping products that have commercial and/or academic import. Since the field of sUAS applications is just a few years old, this book covers the need for a compendium of case studies to guide the planning, data collection, and most importantly data processing and map error issues, with the range of sensors available to the user community. Written by experienced academics and professionals, this book serves as a guide on how to formulate sUAS based projects, from choice of a sUAS, flight planning for a particular application, sensors and data acquisition, data processing software, mapping software and use of the high spatial resolution maps produced for particular types of geospatial modeling. Features: Focus on sUAS based data acquisition and processing into map products Broad range of case studies by highly experienced academics Practical guidance on sUAS hardware, sensors, and software utilized Compilation of workflow insights from expert professors and professionals Relevant to academia, government, and industry Positional and thematic map accuracy, UAS curriculum development and workflow replicability issues This book would be an excellent text for upper-level undergraduate to graduate level sUAS mapping application courses. It is also invaluable as a reference for educators designing sUAS based curriculum as well as for potential sUAS users to assess the scope of mapping projects that can be done with this technology.
Categories: Science

Unmanned Aircraft Systems Traffic Management

Unmanned Aircraft Systems Traffic Management

As much as I think approaches like deep reinforcement learning can revolutionize complex autonomous systems, we still have a long way to go in ensuring that the neural networks that are foundational to these approaches can be properly ...

Author: Michael S. Baum

Publisher: CRC Press

ISBN: 9781000379556

Category: Technology & Engineering

Page: 347

View: 696

This book introduces unmanned aircraft systems traffic management (UTM) and how this new paradigm in traffic management integrates unmanned aircraft operations into national airspace systems. Exploring how UTM is expected to operate, including possible architectures for UTM implementations, and UTM services, including flight planning, strategic coordination, and conformance monitoring, Unmanned Aircraft Systems Traffic Management: UTM considers the boundaries of UTM and how it is expected to interlace with tactical coordination systems to maintain airspace safety. The book also presents the work of the global ecosystem of players advancing UTM, including relevant standards development organizations (SDOs), and considers UTM governance paradigms and challenges. FEATURES Describes UTM concept of operations (ConOps) and global variations in architectures Explores envisioned UTM services, including flight planning, strategic coordination, conformance monitoring, contingency management, constraints and geo-awareness, and remote identification Highlights cybersecurity standards development and awareness Covers approaches to the approval, management, and oversight of UTM components and ecosystem Considers the future of UTM and potential barriers to its success, international coordination, and regulatory reform This book is an essential, in-depth, annotated resource for developers, unmanned aircraft system operators, pilots, policy makers, researchers, and academics engaged in unmanned systems, transportation management, and the future of aviation.
Categories: Technology & Engineering

Proceedings of the 12th National Technical Seminar on Unmanned System Technology 2020

Proceedings of the 12th National Technical Seminar on Unmanned System Technology 2020

System. Using. Face. Recognition. with. Deep. Learning. Algorithm. Ibrahim Al-Amoudi, Rosdiyana Samad, Nor Rul Hasma ... Proceedings of the 12th National Technical Seminar on Unmanned System Technology 2020, Lecture Notes in Electrical ...

Author: Khalid Isa

Publisher: Springer Nature

ISBN: 9789811624063

Category: Technology & Engineering

Page: 1195

View: 212

This book comprises the proceedings of the 12th National Technical Symposium on Unmanned System Technology 2020 (NUSYS’20) held on October 27–28, 2020. It covers a number of topics, including intelligent robotics, novel sensor technology, control algorithms, acoustics signal processing, imaging techniques, biomimetic robots, green energy sources, and underwater communication backbones and protocols, and it appeals to researchers developing marine technology solutions and policy-makers interested in technologies to facilitate the exploration of coastal and oceanic regions.
Categories: Technology & Engineering

Environmental Perception Technology for Unmanned Systems

Environmental Perception Technology for Unmanned Systems

Unmanned. Systems. 1.1. Introduction. Since the beginning of the 21st century, research in the intelligent systems had ... in the field of deep learning, neural network and other artificial intelligence, had seen incredible advancement.

Author: Xin Bi

Publisher: Springer Nature

ISBN: 9789811580932

Category: Technology & Engineering

Page: 252

View: 433

This book focuses on the principles and technology of environmental perception in unmanned systems. With the rapid development of a new generation of information technologies such as automatic control and information perception, a new generation of robots and unmanned systems will also take on new importance. This book first reviews the development of autonomous systems and subsequently introduces readers to the technical characteristics and main technologies of the sensor. Lastly, it addresses aspects including autonomous path planning, intelligent perception and autonomous control technology under uncertain conditions. For the first time, the book systematically introduces the core technology of autonomous system information perception.
Categories: Technology & Engineering

Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques

Unmanned Aerial Vehicles and Multidisciplinary Applications Using AI Techniques

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 ...

Author: Thusnavis, Bella Mary I.

Publisher: IGI Global

ISBN: 9781799887652

Category: Computers

Page: 325

View: 469

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.
Categories: Computers