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  • 1
    Book
    Book
    Nanchang : Jiangxi Jiaoyu Chubanshe
    UID:
    (DE-605)HT003600087
    Format: Getr. Zählung
    Edition: 1 ban, 1 yinshua
    ISBN: 7539208112
    Note: In chines. Schr
    Language: Undetermined
    Keywords: China ; Sprache ; Chinesisch
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  • 2
    UID:
    (DE-603)326028943
    Format: XXVIII, 198 Seiten , Illustrationen, Diagramme , 25 cm
    ISBN: 9781118122761 , 1118122763
    Series Statement: IEEE Press series on systems science and engineering 3
    Note: Literaturangaben
    Language: English
    Subjects: Engineering , Geography
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  • 3
    Book
    Book
    New York, NY : Wiley, J | Piscataway, NJ : IEEE Press
    UID:
    (DE-604)BV043951023
    Format: xxviii, 198 Seiten , Illustrationen, Diagramme
    Edition: 1., Auflage
    ISBN: 9781118122761 , 1118122763
    Series Statement: IEEE Series on Systems Science and Engineering
    Language: English
    Subjects: Geography
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  • 4
    Online Resource
    Online Resource
    Piscataway, N.J. : IEEE Press | Hoboken, N.J. : Wiley
    UID:
    (DE-627)1653179147
    Format: Online-Ressource (xviii, 324 S.)
    Edition: Wiley Online Library
    ISBN: 9781118377178
    Series Statement: IEEE Press Series on Systems Science and Engineering
    Note: includes bibliography, references and index
    Additional Edition: 9781118122761
    Language: English
    Subjects: Engineering
    RVK:
    Keywords: Sensortechnik
    URL: Cover
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  • 5
    Online Resource
    Online Resource
    Hoboken, New Jersey : Wiley-IEEE Press | Hoboken, NJ : John Wiley & Sons, Inc.
    UID:
    (DE-603)364879505
    Format: 1 Online-Ressource (xxviii, 198 Seiten) , Illustrationen.
    ISBN: 9781118377178 , 1118377176 , 9781118377185 , 1118377184 , 9781283941273 , 1283941279
    Series Statement: IEEE Press series on systems science and engineering
    Content: "Unmanned systems and robotics technologies have become very popular recently owing to their ability to replace human beings in dangerous, tedious, or repetitious jobs. This book fill the gap in the field between research and real-world applications, providing scientists and engineers with essential information on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes. Target scenarios include environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks"--...
    Content: "This book will stimulate other researchers in this field to work on more practical questions and provide some insights to industrial engineers who want to use unmanned systems for their application problems"--...
    Note: Includes bibliographical references and index
    Additional Edition: 9781118122761
    Additional Edition: 1118122763
    Language: English
    Subjects: Engineering , Geography
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  • 6
    Online Resource
    Online Resource
    New York, NY : John Wiley & Sons
    UID:
    (DE-101)1064010814
    Format: Online-Ressource
    Edition: 1., Auflage
    ISBN: 9781118377161 , 1118377168
    Series Statement: IEEE Series on Systems Science and Engineering
    Note: Lizenzpflichtig
    Additional Edition: Druckausg. 9781118122761
    Language: English
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  • 7
    Online Resource
    Online Resource
    New York, NY : John Wiley & Sons
    UID:
    (DE-101)1064010849
    Format: Online-Ressource
    Edition: 1., Auflage
    ISBN: 9781118377185 , 1118377184
    Series Statement: IEEE Series on Systems Science and Engineering
    Note: Lizenzpflichtig
    Additional Edition: Druckausg. 9781118122761
    Language: English
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  • 8
    Online Resource
    Online Resource
    Hoboken, NJ : Wiley | Piscataway, NJ : IEEE Press
    UID:
    (DE-604)BV041413634
    Format: 1 Online-Ressource
    ISBN: 9781118377178 , 9781118122761
    Series Statement: IEEE Press series on systems science and engineering [2]
    Note: "Unmanned systems and robotics technologies have become very popular recently owing to their ability to replace human beings in dangerous, tedious, or repetitious jobs. This book fill the gap in the field between research and real-world applications, providing scientists and engineers with essential information on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes. Target scenarios include environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks"--
    Language: English
    Subjects: Engineering , Geography
    RVK:
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    RVK:
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  • 9
    Online Resource
    Online Resource
    Hoboken, New Jersey : Wiley-IEEE Press
    UID:
    (DE-627)876679602
    Format: Online Ressource (xxviii, 198 pages) , illustrations (some color).
    Edition: Online-Ausg. Also available in print
    ISBN: 1118377184 , 9781283941273 , 1283941279 , 9781118377178 , 1118377176 , 9781118377185 , 9781118122761
    Series Statement: IEEE press series on systems science and engineering 2
    Content: How to design and use unmanned vehicles for remote sensing and actuation-a practical guideOwing to their ability to replace human beings in dangerous, tedious, or repetitive jobs, unmanned systems are increasingly used in river/reservoir surveillance and the monitoring and control of chemical/nuclear leaks. This book presents new and innovative techniques for the design and use of unmanned vehicles for remote sensing and distributed control in agricultural and environmental systems.Focusing on small, unmanned aerial vehicles (UAVs), Remote Sensing and Actuation Using Unmanned Vehicles first describes the design of AggieAir, a low-cost UAV platform for remote sensing. It then explains how to solve state estimation and advanced lateral flight controller design problems in the small UAV platform before examining remote sensing problems with single and multiple UAVs. The book also includes flight test results-building upon these measurements to present actuation algorithms for such missions as diffusion control.Inside, readers will discover:. How to develop low-cost, small unmanned aircraft systems (UAS) for remote sensing applications. What autopilots are available for small UAVs, including a series of flight test protocols for the safe operation of small UAVs. How to design and implement advanced fractional-order controllers for autonomous navigation of UAVs. Voronoi diagram-based cooperative controller design for diffusion control in unmanned vehicles for both sensing and actuation. How to design and validate consensus-based controllers for rendezvous and formation control in unmanned ground vehiclesIncluding an appendix with IMU communication protocols and Paparazzi UAV code modification guides, Remote Sensing and Actuation Using Unmanned Vehicles is an invaluable guide for scientists and engineers in remote sensing, aerospace, robotics, and autonomous control
    Content: 3.3 Low-Cost Inertial Measurement Units: Hardware and Sensor Suites 60 -- 3.3.1 IMU Basics and Notations 60 -- 3.3.2 Sensor Packs 61 -- 3.3.3 IMU Categories 63 -- 3.3.4 Example Low-Cost IMUs 63 -- 3.4 Attitude Estimation Using Complementary Filters on SO(3) 65 -- 3.4.1 Passive Complementary Filter 66 -- 3.4.2 Explicit Complementary Filter 66 -- 3.4.3 Flight Test Results 67 -- 3.5 Attitude Estimation Using Extended Kalman Filters 68 -- 3.5.1 General Extended Kalman Filter 68 -- 3.5.2 Quaternion-Based Extended Kalman Filter 69 -- 3.5.3 Euler Angles-Based Extended Kalman Filter 69 -- 3.6 AggieEKF: GPS-Aided Extended Kalman Filter 70 -- 3.7 Chapter Summary 74 -- References 74 -- 4 Lateral Channel Fractional Order Flight Controller Design for a Small UAV 77 -- 4.1 Introduction 77 -- 4.2 Preliminaries of UAV Flight Control 78 -- 4.3 Roll-Channel System Identification and Control 79 -- 4.3.1 System Model 80 -- 4.3.2 Excitation Signal for System Identification 80 -- 4.3.3 Parameter Optimization 81 -- 4.4 Fractional Order Controller Design 81 -- 4.4.1 Fractional Order Operators 81 -- 4.4.2 PI(Sn(B Controller Design 82 -- 4.4.3 Fractional Order Controller Implementation 85 -- 4.5 Simulation Results 86 -- 4.5.1 Introduction to Aerosim Simulation Platform 87 -- 4.5.2 Roll-Channel System Identification 87 -- 4.5.3 Fractional-Order PI Controller Design Procedure 89 -- 4.5.4 Integer-Order PID Controller Design 90 -- 4.5.5 Comparison 90 -- 4.6 UAV Flight Testing Results 92 -- 4.6.1 The ChangE UAV Platform 92 -- 4.6.2 System Identification 94 -- 4.6.3 Proportional Controller and Integer Order PI Controller Design 96 -- 4.6.4 Fractional Order PI Controller Design 97 -- 4.6.5 Flight Test Results 98 -- 4.7 Chapter Summary 99 -- References 99 -- 5 Remote Sensing Using Single Unmanned Aerial Vehicle 101 -- 5.1 Motivations for Remote Sensing 102 -- 5.1.1 Water Management and Irrigation Control Requirements 102 -- 5.1.2 Introduction of Remote Sensing 102 -- 5.2 Remote Sensing Using Small UAVs 103
    Content: 5.2.1 Coverage Control 103 -- 5.2.2 Georeference Problem 105 -- 5.3 Sample Applications for AggieAir UAS 109 -- 5.3.1 Real-Time Surveillance 109 -- 5.3.2 Farmland Coverage 109 -- 5.3.3 Road Surveying 111 -- 5.3.4 Water Area Coverage 112 -- 5.3.5 Riparian Surveillance 112 -- 5.3.6 Remote Data Collection 115 -- 5.3.7 Other Applications 116 -- 5.4 Chapter Summary 119 -- References 119 -- 6 Cooperative Remote Sensing Using Multiple Unmanned Vehicles 121 -- 6.1 Consensus-Based Formation Control 122 -- 6.1.1 Consensus Algorithms 122 -- 6.1.2 Implementation of Consensus Algorithms 123 -- 6.1.3 MASnet Hardware Platform 123 -- 6.1.4 Experimental Results 125 -- 6.2 Surface Wind Profile Measurement Using Multiple UAVs 129 -- 6.2.1 Problem Definition: Wind Profile Measurement 131 -- 6.2.2 Wind Profile Measurement Using UAVs 133 -- 6.2.3 Wind Profile Measurement Using Multiple UAVs 135 -- 6.2.4 Preliminary Simulation and Experimental Results 136 -- 6.3 Chapter Summary 140 -- References 140 -- 7 Diffusion Control Using Mobile Sensor and Actuator Networks 143 -- 7.1 Motivation and Background 143 -- 7.2 Mathematical Modeling and Problem Formulation 144 -- 7.3 CVT-Based Dynamical Actuator Motion Scheduling Algorithm 146 -- 7.3.1 Motion Planning for Actuators with the First-Order Dynamics 146 -- 7.3.2 Motion Planning for Actuators with the Second-Order Dynamics 147 -- 7.3.3 Neutralizing Control 147 -- 7.4 Grouping Effect in CVT-Based Diffusion Control 147 -- 7.4.1 Grouping for CVT-Based Diffusion Control 148 -- 7.4.2 Diffusion Control Simulation with Different Group Sizes 148 -- 7.4.3 Grouping Effect Summary 150 -- 7.5 Information Consensus in CVT-Based Diffusion Control 154 -- 7.5.1 Basic Consensus Algorithm 154 -- 7.5.2 Requirements of Diffusion Control 154 -- 7.5.3 Consensus-Based CVT Algorithm 155 -- 7.6 Simulation Results 158 -- 7.7 Chapter Summary 164 -- References 164 -- 8 Conclusions and Future Research Suggestions 167 -- 8.1 Conclusions 167 -- 8.2 Future Research Suggestions 168
    Content: 8.2.1 VTOL UAS Design for Civilian Applications 168 -- 8.2.2 Monitoring and Control of Fast-Evolving Processes 169 -- 8.2.3 Other Future Research Suggestions 169 -- References 170 -- Appendix 171 -- A.1 List of Documents for CSOIS Flight Test Protocol 171 -- A.1.1 Sample CSOIS-OSAM Flight Test Request Form 171 -- A.1.2 Sample CSOIS-OSAM 48 in. UAV (IR) In-lab Inspection Form 172 -- A.1.3 Sample Preflight Checklist 172 -- A.2 IMU/GPS Serial Communication Protocols 173 -- A.2.1 u-blox GPS Serial Protocol 173 -- A.2.2 Crossbow MNAV IMU Serial Protocol 173 -- A.2.3 Microstrain GX2 IMU Serial Protocol 174 -- A.2.4 Xsens Mti-g IMU Serial Protocol 178 -- A.3 Paparazzi Autopilot Software Architecture: A Modification Guide 182 -- A.3.1 Autopilot Software Structure 182 -- A.3.2 Airborne C Files 183 -- A.3.3 OSAM-Paparazzi Interface Implementation 184 -- A.3.4 Configuration XML Files 185 -- A.3.5 Roll-Channel Fractional Order Controller Implementation 189 -- A.4 DiffMas2D Code Modification Guide 192 -- A.4.1 Files Description 192 -- A.4.2 Diffusion Animation Generation 193 -- A.4.3 Implementation of CVT-Consensus Algorithm 193 -- References 195 -- Topic Index 197
    Content: List of Figures xv -- List of Tables xix -- Foreword xxi -- Preface xxiii -- Acknowledgments xxv -- Acronyms xxvii -- 1 Introduction 1 -- 1.1 Monograph Roadmap 1 -- 1.1.1 Sensing and Control in the Information-Rich World 1 -- 1.1.2 Typical Civilian Application Scenarios 3 -- 1.1.3 Challenges in Sensing and Control Using Unmanned Vehicles 5 -- 1.2 Research Motivations 7 -- 1.2.1 Small Unmanned Aircraft System Design for Remote Sensing 7 -- 1.2.2 State Estimation for Small UAVs 8 -- 1.2.3 Advanced Flight Control for Small UAVs 9 -- 1.2.4 Cooperative Remote Sensing Using Multiple UAVs 10 -- 1.2.5 Diffusion Control Using Mobile Actuator and Sensor Networks 11 -- 1.3 Monograph Contributions 11 -- 1.4 Monograph Organization 12 -- References 12 -- 2 AggieAir: A Low-Cost Unmanned Aircraft System for Remote Sensing 15 -- 2.1 Introduction 15 -- 2.2 Small UAS Overview 17 -- 2.2.1 Autopilot Hardware 19 -- 2.2.2 Autopilot Software 21 -- 2.2.3 Typical Autopilots for Small UAVs 22 -- 2.3 AggieAir UAS Platform 26 -- 2.3.1 Remote Sensing Requirements 26 -- 2.3.2 AggieAir System Structure 27 -- 2.3.3 Flying-Wing Airframe 30 -- 2.3.4 OSAM-Paparazzi Autopilot 31 -- 2.3.5 OSAM Image Payload Subsystem 32 -- 2.3.6 gRAID Image Georeference Subsystem 36 -- 2.4 OSAM-Paparazzi Interface Design for IMU Integration 39 -- 2.4.1 Hardware Interface Connections 40 -- 2.4.2 Software Interface Design 41 -- 2.5 AggieAir UAS Test Protocol and Tuning 45 -- 2.5.1 AggieAir UAS Test Protocol 45 -- 2.5.2 AggieAir Controller Tuning Procedure 46 -- 2.6 Typical Platforms and Flight Test Results 47 -- 2.6.1 Typical Platforms 47 -- 2.6.2 Flight Test Results 48 -- 2.7 Chapter Summary 50 -- References 50 -- 3 Attitude Estimation Using Low-Cost IMUs for Small Unmanned Aerial Vehicles 53 -- 3.1 State Estimation Problem Definition 54 -- 3.2 Rigid Body Rotations Basics 55 -- 3.2.1 Frame Definition 55 -- 3.2.2 Rotation Representations 56 -- 3.2.3 Conversion Between Rotation Representations 57 -- 3.2.4 UAV Kinematics 58
    Note: Includes bibliographical references and index. - Description based on print version record , Restricted to subscribers or individual electronic text purchasers , AggieAir: A Low-Cost Unmanned Aircraft System for Remote SensingAttitude Estimation Using Low-Cost IMUs for Small Unmanned Aerial Vehicles -- Lateral Channel Fractional Order Flight Controller Design for a Small UAV -- Remote Sensing Using Single Unmanned Aerial Vehicle -- Cooperative Remote Sensing Using Multiple Unmanned Vehicles -- Diffusion Control Using Mobile Sensor and Actuator Networks -- Conclusions and Future Research Suggestions. , Also available in print. , Mode of access: World Wide Web.
    Additional Edition: 9781118122761
    Additional Edition: Druckausg. 978-111-812-276-1
    Additional Edition: Print version 9781118122761
    Additional Edition: Erscheint auch als Druck-Ausgabe Chao, Haiyang Remote sensing and actuation using unmanned vehicles Piscataway, NJ : IEEE Press, 2012 9781118122761
    Language: English
    Subjects: Engineering , Geography
    RVK:
    RVK:
    RVK:
    RVK:
    Keywords: Electronic books ; Electronic books
    URL: Cover
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  • 10
    Online Resource
    Online Resource
    Hoboken, New Jersey : Wiley-IEEE Press
    UID:
    (DE-627)1679600621
    Format: 1 Online-Ressource (xxviii, 198 pages) , illustrations (some color)
    ISBN: 1118377176 , 1118377184 , 1283941279 , 9781118377185 , 9781283941273 , 9781118377178
    Series Statement: IEEE Press series on systems science and engineering
    Content: "This book will stimulate other researchers in this field to work on more practical questions and provide some insights to industrial engineers who want to use unmanned systems for their application problems"--
    Content: "Unmanned systems and robotics technologies have become very popular recently owing to their ability to replace human beings in dangerous, tedious, or repetitious jobs. This book fill the gap in the field between research and real-world applications, providing scientists and engineers with essential information on how to design and employ networked unmanned vehicles for remote sensing and distributed control purposes. Target scenarios include environmental or agricultural applications such as river/reservoir surveillance, wind profiling measurement, and monitoring/control of chemical leaks"--
    Content: AggieAir: A Low-Cost Unmanned Aircraft System for Remote Sensing --Attitude Estimation Using Low-Cost IMUs for Small Unmanned Aerial Vehicles --Lateral Channel Fractional Order Flight Controller Design for a Small UAV --Remote Sensing Using Single Unmanned Aerial Vehicle --Cooperative Remote Sensing Using Multiple Unmanned Vehicles --Diffusion Control Using Mobile Sensor and Actuator Networks --Conclusions and Future Research Suggestions.
    Content: Machine generated contents note:1.Introduction --1.1.Monograph Roadmap --1.1.1.Sensing and Control in the Information-Rich World --1.1.2.Typical Civilian Application Scenarios --1.1.3.Challenges in Sensing and Control Using Unmanned Vehicles --1.2.Research Motivations --1.2.1.Small Unmanned Aircraft System Design for Remote Sensing --1.2.2.State Estimation for Small UAVs --1.2.3.Advanced Flight Control for Small UAVs --1.2.4.Cooperative Remote Sensing Using Multiple UAVs --1.2.5.Diffusion Control Using Mobile Actuator and Sensor Networks --1.3.Monograph Contributions --1.4.Monograph Organization --References --2.AggieAir: A Low-Cost Unmanned Aircraft System for Remote Sensing --2.1.Introduction --2.2.Small UAS Overview --2.2.1.Autopilot Hardware --2.2.2.Autopilot Software --2.2.3.Typical Autopilots for Small UAVs --2.3.AggieAir UAS Platform --2.3.1.Remote Sensing Requirements --2.3.2.AggieAir System Structure --2.3.3.Flying-Wing Airframe --2.3.4.OSAM-Paparazzi Autopilot --2.3.5.OSAM Image Payload Subsystem --2.3.6.gRAID Image Georeference Subsystem --2.4.OSAM-Paparazzi Interface Design for IMU Integration --2.4.1.Hardware Interface Connections --2.4.2.Software Interface Design --2.5.AggieAir UAS Test Protocol and Tuning --2.5.1.AggieAir UAS Test Protocol --2.5.2.AggieAir Controller Tuning Procedure --2.6.Typical Platforms and Flight Test Results --2.6.1.Typical Platforms --2.6.2.Flight Test Results --2.7.Chapter Summary --References --3.Attitude Estimation Using Low-Cost IMUs for Small Unmanned Aerial Vehicles --3.1.State Estimation Problem Definition --3.2.Rigid Body Rotations Basics --3.2.1.Frame Definition --3.2.2.Rotation Representations --3.2.3.Conversion Between Rotation Representations --3.2.4.UAV Kinematics --3.3.Low-Cost Inertial Measurement Units: Hardware and Sensor Suites --3.3.1.IMU Basics and Notations --3.3.2.Sensor Packs --3.3.3.IMU Categories --3.3.4.Example Low-Cost IMUs --3.4.Attitude Estimation Using Complementary Filters on SO(3) --3.4.1.Passive Complementary Filter --3.4.2.Explicit Complementary Filter --3.4.3.Flight Test Results --3.5.Attitude Estimation Using Extended Kalman Filters --3.5.1.General Extended Kalman Filter --3.5.2.Quaternion-Based Extended Kalman Filter --3.5.3.Euler Angles-Based Extended Kalman Filter --3.6.AggieEKF: GPS-Aided Extended Kalman Filter --3.7.Chapter Summary --References --4.Lateral Channel Fractional Order Flight Controller Design for a Small UAV --4.1.Introduction --4.2.Preliminaries of UAV Flight Control --4.3.Roll-Channel System Identification and Control --4.3.1.System Model --4.3.2.Excitation Signal for System Identification --4.3.3.Parameter Optimization --4.4.Fractional Order Controller Design --4.4.1.Fractional Order Operators --4.4.2.PIλ Controller Design --4.4.3.Fractional Order Controller Implementation --4.5.Simulation Results --4.5.1.Introduction to Aerosim Simulation Platform --4.5.2.Roll-Channel System Identification --4.5.3.Fractional-Order PI Controller Design Procedure --4.5.4.Integer-Order PID Controller Design --4.5.5.Comparison --4.6.UAV Flight Testing Results --4.6.1.ChangE UAV Platform --4.6.2.System Identification --4.6.3.Proportional Controller and Integer Order PI Controller Design --4.6.4.Fractional Order PI Controller Design --4.6.5.Flight Test Results --4.7.Chapter Summary --References --5.Remote Sensing Using Single Unmanned Aerial Vehicle --5.1.Motivations for Remote Sensing --5.1.1.Water Management and Irrigation Control Requirements --5.1.2.Introduction of Remote Sensing --5.2.Remote Sensing Using Small UAVs --5.2.1.Coverage Control --5.2.2.Georeference Problem --5.3.Sample Applications for AggieAir UAS --5.3.1.Real-Time Surveillance --5.3.2.Farmland Coverage --5.3.3.Road Surveying --5.3.4.Water Area Coverage --5.3.5.Riparian Surveillance --5.3.6.Remote Data Collection --5.3.7.Other Applications --5.4.Chapter Summary --References --6.Cooperative Remote Sensing Using Multiple Unmanned Vehicles --6.1.Consensus-Based Formation Control --6.1.1.Consensus Algorithms --6.1.2.Implementation of Consensus Algorithms --6.1.3.MASnet Hardware Platform --6.1.4.Experimental Results --6.2.Surface Wind Profile Measurement Using Multiple UAVs --6.2.1.Problem Definition: Wind Profile Measurement --6.2.2.Wind Profile Measurement Using UAVs --6.2.3.Wind Profile Measurement Using Multiple UAVs --6.2.4.Preliminary Simulation and Experimental Results --6.3.Chapter Summary --References --7.Diffusion Control Using Mobile Sensor and Actuator Networks --7.1.Motivation and Background --7.2.Mathematical Modeling and Problem Formulation --7.3.CVT-Based Dynamical Actuator Motion Scheduling Algorithm --7.3.1.Motion Planning for Actuators with the First-Order Dynamics --7.3.2.Motion Planning for Actuators with the Second-Order Dynamics --7.3.3.Neutralizing Control --7.4.Grouping Effect in CVT-Based Diffusion Control --7.4.1.Grouping for CVT-Based Diffusion Control --7.4.2.Diffusion Control Simulation with Different Group Sizes --7.4.3.Grouping Effect Summary --7.5.Information Consensus in CVT-Based Diffusion Control --7.5.1.Basic Consensus Algorithm --7.5.2.Requirements of Diffusion Control --7.5.3.Consensus-Based CVT Algorithm --7.6.Simulation Results --7.7.Chapter Summary --References --8.Conclusions and Future Research Suggestions --8.1.Conclusions --8.2.Future Research Suggestions --8.2.1.VTOL UAS Design for Civilian Applications --8.2.2.Monitoring and Control of Fast-Evolving Processes --8.2.3.Other Future Research Suggestions --References --Appendix --A.1.List of Documents for CSOIS Flight Test Protocol --A.1.1.Sample CSOIS-OSAM Flight Test Request Form --A.1.2.Sample CSOIS-OSAM 48 in. UAV (IR) In-lab Inspection Form --A.1.3.Sample Preflight Checklist --A.2.IMU/GPS Serial Communication Protocols --A.2.1.u-blox GPS Serial Protocol --A.2.2.Crossbow MNAV IMU Serial Protocol --A.2.3.Microstrain GX2 IMU Serial Protocol --A.2.4.Xsens Mti-g IMU Serial Protocol --A.3.Paparazzi Autopilot Software Architecture: A Modification Guide --A.3.1.Autopilot Software Structure --A.3.2.Airborne C Files --A.3.3.OSAM-Paparazzi Interface Implementation --A.3.4.Configuration XML Files --A.3.5.Roll-Channel Fractional Order Controller Implementation --A.4.DiffMas2D Code Modification Guide --A.4.1.Files Description --A.4.2.Diffusion Animation Generation --A.4.3.Implementation of CVT-Consensus Algorithm --References.
    Note: Includes bibliographical references and index
    Additional Edition: 9781118122761
    Additional Edition: Erscheint auch als Druck-Ausgabe Chao, Haiyang Remote sensing and actuation using networked unmanned vehicles Hoboken, New Jersey : Wiley-IEEE Press, ©2012
    Language: English
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