Author: Diego Pizzocaro Publisher: ISBN: Category : Languages : en Pages :
Book Description
A sensor network often consists of a large number of sensing devices of different types. Upon deployment in the field, these sensing devices form an ad hoc network using wireless links or cables to communicate with each other. Sensor networks are increasingly used to support emergency responders in the field usually requiring many sensing tasks to be supported at the same time. By a sensing task we mean any job that requires some amount of sensing resources to be accomplished such as localizing persons in need of help or detecting an event. Tasks might share the usage of a sensor, but more often compete to exclusively control it because of the limited number of sensors and overlapping needs with other tasks. Sensors are in fact scarce and in high demand. In such cases, it might not be possible to satisfy the requirements of all tasks using available sensors. Therefore, the fundamental question to answer is: "Which sensor should be allocated to which task?", which summarizes the Multi-Sensor Task Allocation (MSTA) problem. We focus on a particular MSTA instance where the environment does not provide enough information to plan for future allocations constraining us to perform instantaneous allocation. We look at this problem in both static setting, where all task requests from emergency responders arrive at once, and dynamic setting, where tasks arrive and depart over time. We provide novel solutions based on centralized and distributed approaches. We evaluate their performance using mainly simulations on randomly generated problem instances; moreover, for the dynamic setting, we consider also feasibility of deploying part of the distributed allocation system on user mobile devices. Our solutions scale well with different number of task requests and manage to improve the utility of the network, prioritizing the most important tasks.
Author: Itshak Tkach Publisher: Springer Nature ISBN: 3030347354 Category : Technology & Engineering Languages : en Pages : 145
Book Description
Today’s real-world problems and applications in sensory systems and target detection require efficient, comprehensive and fault-tolerant multi-sensor allocation. This book presents the theory and applications of novel methods developed for such sophisticated systems. It discusses the advances in multi-agent systems and AI along with collaborative control theory and tools. Further, it examines the formulation and development of an allocation framework for heterogeneous multi-sensor systems for various real-world problems that require sensors with different performances to allocate multiple tasks, with unknown a priori priorities that arrive at unknown locations at unknown time. It demonstrates how to decide which sensor to allocate to which tasks when and where. Lastly, it explains the reliability and availability issues of task allocation systems, and includes methods for their optimization. The presented methods are explained, measured, and evaluated by extensive simulations, and the results of these simulations are presented in this book. This book is an ideal resource for academics, researchers and graduate students as well as engineers and professionals and is relevant for various applications such as sensor network design, multi-agent systems, task allocation, target detection, and team formation.
Author: Clare Dixon Publisher: Springer ISBN: 3319224166 Category : Computers Languages : en Pages : 324
Book Description
This book constitutes the refereed proceedings of the 16th Annual Conference on Towards Autonomous Robotics, TAROS 2015, held in Liverpool UK, in September 2015. The 16 revised full papers presented together with 18 short papers were carefully reviewed and selected from 59 submissions. The overall program covers various aspects of robotics, including navigation, planning, sensing and perception, flying and swarm robots, ethics, humanoid robotics, human-robot interaction, and social robotics.
Author: Anis Koubâa Publisher: Springer ISBN: 3319182994 Category : Technology & Engineering Languages : en Pages : 274
Book Description
This book compiles some of the latest research in cooperation between robots and sensor networks. Structured in twelve chapters, this book addresses fundamental, theoretical, implementation and experimentation issues. The chapters are organized into four parts namely multi-robots systems, data fusion and localization, security and dependability, and mobility.
Author: Robin R. Murphy Publisher: MIT Press ISBN: 026203848X Category : Computers Languages : en Pages : 649
Book Description
A comprehensive survey of artificial intelligence algorithms and programming organization for robot systems, combining theoretical rigor and practical applications. This textbook offers a comprehensive survey of artificial intelligence (AI) algorithms and programming organization for robot systems. Readers who master the topics covered will be able to design and evaluate an artificially intelligent robot for applications involving sensing, acting, planning, and learning. A background in AI is not required; the book introduces key AI topics from all AI subdisciplines throughout the book and explains how they contribute to autonomous capabilities. This second edition is a major expansion and reorganization of the first edition, reflecting the dramatic advances made in AI over the past fifteen years. An introductory overview provides a framework for thinking about AI for robotics, distinguishing between the fundamentally different design paradigms of automation and autonomy. The book then discusses the reactive functionality of sensing and acting in AI robotics; introduces the deliberative functions most often associated with intelligence and the capability of autonomous initiative; surveys multi-robot systems and (in a new chapter) human-robot interaction; and offers a “metaview” of how to design and evaluate autonomous systems and the ethical considerations in doing so. New material covers locomotion, simultaneous localization and mapping, human-robot interaction, machine learning, and ethics. Each chapter includes exercises, and many chapters provide case studies. Endnotes point to additional reading, highlight advanced topics, and offer robot trivia.
Author: Anis Koubâa Publisher: Springer ISBN: 3642393012 Category : Technology & Engineering Languages : en Pages : 103
Book Description
Mobile robots and Wireless Sensor Networks (WSNs) have enabled great potentials and a large space for ubiquitous and pervasive applications. Robotics and WSNs 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 primary objective of book is to provide a reference for cutting-edge studies and research trends pertaining to robotics and sensor networks, and in particular for the coupling between them. The book consists of five chapters. The first chapter presents a cooperation strategy for teams of multiple autonomous vehicles to solve the rendezvous problem. The second chapter is motivated by the need to improve existing solutions that deal with connectivity prediction, and proposed a genetic machine learning approach for link-quality prediction. The third chapter presents an architecture for indoor navigation using an Android smartphone for guiding a variety of users, from sighted to the visually impaired, to their intended destination. In chapter four, the authors deal with accurate prediction modeling of ocean currents for underwater glider navigation. In chapter five, the authors discuss the challenges and limitations of RSS-based localization mechanisms and propose, EasyLoc, an autonomous and practical RSS-based localization technique that satisfies ease of deployment and implementation.
Author: Xue-Bo Jin Publisher: MDPI ISBN: 3039283022 Category : Technology & Engineering Languages : en Pages : 602
Book Description
This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.
Author: Frans A. Oliehoek Publisher: Springer ISBN: 3319289292 Category : Computers Languages : en Pages : 146
Book Description
This book introduces multiagent planning under uncertainty as formalized by decentralized partially observable Markov decision processes (Dec-POMDPs). The intended audience is researchers and graduate students working in the fields of artificial intelligence related to sequential decision making: reinforcement learning, decision-theoretic planning for single agents, classical multiagent planning, decentralized control, and operations research.
Author: Shaoshan Liu Publisher: Morgan & Claypool Publishers ISBN: 1681731673 Category : Computers Languages : en Pages : 285
Book Description
This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions about its actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, we are able to test new algorithms and update the HD map—plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find plenty of references for an effective, deeper exploration of the various technologies.
Author: Diego Pizzocaro
Author: Itshak Tkach
Author: Clare Dixon
Author: Anis Koubâa
Author: Robin R. Murphy
Author: Anis Koubâa
Author: Xue-Bo Jin
Author: 
Author: Frans A. Oliehoek
Author: Shaoshan Liu