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E-BookPDF1 - PDF WatermarkE-Book
316 Seiten
Englisch
Springer Berlin Heidelbergerschienen am23.10.20092010
Flying insects are intelligent micromachines capable of exquisite maneuvers in unpredictable environments. Understanding these systems advances our knowledge of flight control, sensor suites, and unsteady aerodynamics, which is of crucial interest to engineers developing intelligent flying robots or micro air vehicles (MAVs). The insights we gain when synthesizing bioinspired systems can in turn benefit the fields of neurophysiology, ethology and zoology by providing real-life tests of the proposed models.



This book was written by biologists and engineers leading the research in this crossdisciplinary field. It examines all aspects of the mechanics, technology and intelligence of insects and insectoids. After introductory-level overviews of flight control in insects, dedicated chapters focus on the development of autonomous flying systems using biological principles to sense their surroundings and autonomously navigate. A significant part of the book is dedicated to the mechanics and control of flapping wings both in insects and artificial systems. Finally hybrid locomotion, energy harvesting and manufacturing of small flying robots are covered. A particular feature of the book is the depth on realization topics such as control engineering, electronics, mechanics, optics, robotics and manufacturing.



This book will be of interest to academic and industrial researchers engaged with theory and engineering in the domains of aerial robotics, artificial intelligence, and entomology.



Dario Floreano is the director of the Laboratory of Intelligent Systems at EPFL Lausanne. He has authored books on evolutionary robotics and bio-inspired artificial intelligence, and he has given invited talks on the topic at major conferences in robotics, computational intelligence, artificial life and natural computing. Jean-Christophe Zufferey is a scientist at EPFL Lausanne, specializing on research into aerial, bio-inspired and evolutionary robotics. He founded a company that specializes in educational robotics and indoor flyers, and he has gliding and flying pilot licenses. Mandyam V. Srinivasan heads the Visual and Sensory Neuroscience team at the Queensland Brain Institute. He studies the behaviour of small animals, in particular insects, and seeks to elucidate principles of flight control and navigation, and to explore the limits of the cognitive capacities of small brains. Charlie Ellington is Professor of Animal Mechanics at the University of Cambridge, and his interests are in the fields of biomechanics and comparative physiology, with a particular fascination for animal flight.mehr
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Produkt

KlappentextFlying insects are intelligent micromachines capable of exquisite maneuvers in unpredictable environments. Understanding these systems advances our knowledge of flight control, sensor suites, and unsteady aerodynamics, which is of crucial interest to engineers developing intelligent flying robots or micro air vehicles (MAVs). The insights we gain when synthesizing bioinspired systems can in turn benefit the fields of neurophysiology, ethology and zoology by providing real-life tests of the proposed models.



This book was written by biologists and engineers leading the research in this crossdisciplinary field. It examines all aspects of the mechanics, technology and intelligence of insects and insectoids. After introductory-level overviews of flight control in insects, dedicated chapters focus on the development of autonomous flying systems using biological principles to sense their surroundings and autonomously navigate. A significant part of the book is dedicated to the mechanics and control of flapping wings both in insects and artificial systems. Finally hybrid locomotion, energy harvesting and manufacturing of small flying robots are covered. A particular feature of the book is the depth on realization topics such as control engineering, electronics, mechanics, optics, robotics and manufacturing.



This book will be of interest to academic and industrial researchers engaged with theory and engineering in the domains of aerial robotics, artificial intelligence, and entomology.



Dario Floreano is the director of the Laboratory of Intelligent Systems at EPFL Lausanne. He has authored books on evolutionary robotics and bio-inspired artificial intelligence, and he has given invited talks on the topic at major conferences in robotics, computational intelligence, artificial life and natural computing. Jean-Christophe Zufferey is a scientist at EPFL Lausanne, specializing on research into aerial, bio-inspired and evolutionary robotics. He founded a company that specializes in educational robotics and indoor flyers, and he has gliding and flying pilot licenses. Mandyam V. Srinivasan heads the Visual and Sensory Neuroscience team at the Queensland Brain Institute. He studies the behaviour of small animals, in particular insects, and seeks to elucidate principles of flight control and navigation, and to explore the limits of the cognitive capacities of small brains. Charlie Ellington is Professor of Animal Mechanics at the University of Cambridge, and his interests are in the fields of biomechanics and comparative physiology, with a particular fascination for animal flight.
Details
Weitere ISBN/GTIN9783540893936
ProduktartE-Book
EinbandartE-Book
FormatPDF
Format Hinweis1 - PDF Watermark
FormatE107
Erscheinungsjahr2009
Erscheinungsdatum23.10.2009
Auflage2010
Seiten316 Seiten
SpracheEnglisch
IllustrationenXII, 316 p.
Artikel-Nr.1442295
Rubriken
Genre9200

Inhalt/Kritik

Inhaltsverzeichnis
1;Preface;5
2;Contents;7
3;Contributors;9
4;1 Experimental Approaches Toward a Functional Understanding of Insect Flight Control;13
4.1;1.1 Introduction;13
4.1.1;1.1.1 Chapter Overview;14
4.2;1.2 Low-Level Flight Control Biomechanics of Free Flight;14
4.2.1;1.2.1 Research Background;15
4.2.2;1.2.2 Experiments;15
4.2.2.1;1.2.2.1 Hovering Flight;15
4.2.2.2;1.2.2.2 Maneuvering;17
4.2.3;1.2.3 Conclusions;17
4.3;1.3 Intermediate-Level Flight Control Visuomotor Reflexes;18
4.3.1;1.3.1 Research Background;18
4.3.2;1.3.2 Experiments;18
4.3.2.1;1.3.2.1 System Analysis of Visual Flight Speed Control Using Virtual Reality Display Technology;19
4.3.3;1.3.3 Conclusions;19
4.4;1.4 High-Level Flight Control Landmark-Guided Goal Navigation;20
4.4.1;1.4.1 Research Background;20
4.4.2;1.4.2 Experiments;20
4.4.3;1.4.3 Conclusions;22
4.5;1.5 Closing Words;23
4.6;References;23
5;2 From Visual Guidance in Flying Insects to Autonomous Aerial Vehicles;26
5.1;2.1 Introduction;26
5.2;2.2 Landing on a Horizontal Surface;27
5.3;2.3 Terrain Following;29
5.4;2.4 Practical Problems with the Measurement of Optic Flow;30
5.5;2.5 A Mirror-Based Vision System for Terrain Following and Landing;30
5.6;2.6 Height Estimation and Obstacle Detection During Complex Motions;32
5.7;2.7 Hardware Realization and System Tests;33
5.8;2.8 Extracting Information on Range and Topography;36
5.9;2.9 Preliminary Flight Tests;37
5.10;2.10 Conclusions and Discussion;37
5.11;References;38
6;3 Optic Flow Based Autopilots: Speed Control and Obstacle Avoidance;40
6.1;3.1 Introduction;40
6.2;3.2 From the Fly EMDs to Electronic Optic Flow Sensors;41
6.3;3.3 An Explicit Control Scheme for Ground Avoidance;42
6.3.1;3.3.1 Avoiding the Ground by Sensing the Ventral Optic Flow;43
6.3.2;3.3.2 The ''Optic Flow Regulator'';45
6.3.3;3.3.3 Micro-Helicopter (MH) with a Downward-Looking Optic Flow Sensing Eye;45
6.3.4;3.3.4 Insects' Versus the Seeing Helicopter's Behavioral Patterns;46
6.4;3.4 An Explicit Control Scheme for Speed Control and Lateral Obstacle Avoidance;48
6.4.1;3.4.1 Effects of Lateral OF on Wall Clearance and Forward Speed;48
6.4.2;3.4.2 New Robotic Demonstrator Based on a Hovercraft (HO);48
6.4.3;3.4.3 The LORA III Autopilot: A Dual OF Regulator;50
6.4.3.1;3.4.3.1 Side Control System;50
6.4.3.2;3.4.3.2 Forward Control System;50
6.4.4;3.4.4 ''Operating Point'' of the Dual OF Regulator;51
6.4.5;3.4.5 Simulation Results: Flight Paths Along Straight or Tapered Corridors;52
6.4.5.1;3.4.5.1 Wall-Following Behavior Along a Straight Corridor;52
6.4.5.2;3.4.5.2 ''Centering Behavior'': A Particular Case of ''Wall-Following Behavior'';53
6.4.5.3;3.4.5.3 Flight Pattern Along a Tapered Corridor;54
6.5;3.5 Conclusion ;56
6.5.1;3.5.1 Is There a Pilot Onboard an Insect?;56
6.5.2;3.5.2 Potential Aeronautics and Aerospace Applications;57
6.6;References;58
7;4 Active Vision in Blowflies: Strategies and Mechanisms of Spatial Orientation;62
7.1;4.1 Virtuosic Flight Behaviour: Approaches to Unravel the Underlying Mechanisms;62
7.2;4.2 Active Vision: The Sensory and Motor Side of the Closed ActionPerception Cycle;63
7.3;4.3 Extracting Spatial Information from Actively Generated Optic Flow;66
7.4;4.4 A CyberFly: Performance of Experimentally Established Mechanisms Under Closed-Loop Conditions;68
7.5;4.5 Conclusions;70
7.6;References;70
8;5 Wide-Field Integration Methods for Visuomotor Control;73
8.1;5.1 Introduction;73
8.2;5.2 The Insect Visuomotor System;74
8.3;5.3 Wide-Field Integration of Optic Flow;75
8.4;5.4 Application to a Micro-helicopter;76
8.5;5.5 Summary;80
8.6;References;80
9;6 Optic Flow to Steer and Avoid Collisions in 3D;82
9.1;6.1 Introduction;82
9.2;6.2 Review of Optic Flow-Based Flying Robots;83
9.3;6.3 Optic Flow;85
9.4;6.4 Control Strategy;87
9.5;6.5 Application to a 10-g Indoor Microflyer;89
9.5.1;6.5.1 Platform;89
9.5.2;6.5.2 Control Strategy;91
9.5.3;6.5.3 Results;91
9.6;6.6 Conclusions and Outlook;92
9.7;References;93
10;7 Visual Homing in Insects and Robots;96
10.1;7.1 Homing in Insects;96
10.2;7.2 Probing the Content of Insect Location Memories;97
10.3;7.3 Modelling Homing: Computer Simulations and Robotics Experiments;101
10.4;7.4 Homing in Natural Environments;103
10.5;7.5 Acquisition and Use of Visual Representations;104
10.6;7.6 Outlook;106
10.7;References;107
11;8 Motion Detection Chips for Robotic Platforms;110
11.1;8.1 Introduction;110
11.2;8.2 Algorithms for aVLSI Motion Detection Chips and Their Implementations;111
11.2.1;8.2.1 Gradient-Based Intensity Algorithm;113
11.2.2;8.2.2 Intensity-Based Correlation;115
11.2.3;8.2.3 Token-Based Correlation;115
11.2.4;8.2.4 Time-of-Travel;116
11.3;8.3 Promising Motion Chip Architectures;118
11.4;8.4 Summary;120
11.5;References;121
12;9 Insect-Inspired Odometry by Optic Flow Recorded with Optical Mouse Chips;124
12.1;9.1 Introduction;124
12.2;9.2 Hardware Implementations;125
12.3;9.3 Calibration;125
12.3.1;9.3.1 Head A;126
12.3.2;9.3.2 Head B;126
12.4;9.4 Odometry;127
12.4.1;9.4.1 Head A;128
12.4.2;9.4.2 Head B;129
12.4.3;9.4.3 Fast Estimates;129
12.5;9.5 Tests;129
12.5.1;9.5.1 Head A;130
12.5.2;9.5.2 Head B;130
12.5.2.1;9.5.2.1 Test for the Orientation and Size of the Estimated Rotation;130
12.5.2.2;9.5.2.2 Outdoor Test of T- and Distribution;131
12.5.2.3;9.5.2.3 Test for Evaluations of the Relative Nearness;132
12.6;9.6 Discussion;132
12.7;References;134
13;10 Microoptical Artificial Compound Eyes;136
13.1;10.1 Introduction;136
13.2;10.2 Miniaturization of Imaging Systems;137
13.3;10.3 The Compound Eyes of Insects;138
13.3.1;10.3.1 Apposition Compound Eyes;139
13.3.2;10.3.2 Superposition Compound Eyes;140
13.4;10.4 Insect-Inspired Imaging Systems;140
13.4.1;10.4.1 Artificial Apposition Compound Eyes;141
13.4.1.1;10.4.1.1 Prototype Demonstration;142
13.4.1.2;10.4.1.2 Increased Sensitivity with Artificial Neural Superposition;144
13.4.2;10.4.2 Artificial Superposition Compound Eyes;146
13.4.3;10.4.3 Fabrication of Artificial Compound Eye Optics;148
13.4.4;10.4.4 Future Challenges;149
13.5;References;150
14;11 Flexible Wings and Fluid0Structure Interactions for Micro-Air Vehicles;152
14.1;11.1 Introduction;152
14.2;11.2 Parameter Space and Scaling Laws;155
14.3;11.3 Fixed Membrane Wing MAVs;157
14.4;11.4 Aeroelasticity of Flapping (Plunging) Wings;161
14.5;11.5 Summary and Concluding Remarks;164
14.6;References;165
15;12 Flow Control Using Flapping Wings for an Efficient Low-Speed Micro-Air Vehicle;167
15.1;12.1 Introduction;167
15.2;12.2 Flapping Airfoil Aerodynamics;168
15.3;12.3 Effect of Viscosity on Flapping Airfoil Aerodynamics;170
15.4;12.4 The Bird Wing A Fully Integrated Lift/Propulsion/Control System;172
15.5;12.5 The Oscillating Airfoil A Two-Dimensional Propeller;172
15.6;12.6 Conceptual Design Considerations for a Flapping-Wing MAV;173
15.7;12.7 Summary and Outlook;176
15.8;References;177
16;13 A Passively Stable Hovering Flapping Micro-Air Vehicle;178
16.1;13.1 Introduction;178
16.2;13.2 Aerodynamics of Flapping Flight;179
16.2.1;13.2.1 Passive Wing Pitching;180
16.3;13.3 Machine Design;180
16.3.1;13.3.1 Design Improvements;184
16.4;13.4 Passive Stability;185
16.5;13.5 Performance Results;188
16.5.1;13.5.1 Future Design Changes;189
16.6;13.6 Conclusion;190
16.7;References;190
17;14 The Scalable Design of Flapping Micro-Air Vehicles Inspired by Insect Flight;192
17.1;14.1 Introduction;192
17.2;14.2 The Scalable Wing Aerodynamics of Hovering Insects;193
17.3;14.3 Design Approach: Scale a Flapping MAV That Works Down to Smaller Sizes;194
17.4;14.4 DelFly: A Flapping MAV That Works;194
17.5;14.5 DelFly II: Improved Design;199
17.6;14.6 DelFly II: Aerodynamic Analyses;199
17.6.1;14.6.1 DelFly Models Used for Aerodynamic Measurements;202
17.6.2;14.6.2 Lift as a Function of Flap Frequency at a Constant Flap Angle of 36;203
17.6.3;14.6.3 Lift and Power as a Function of Flap Angle at a Flap Frequency of 14 Hz;204
17.6.4;14.6.4 Power Requirement and Wing Deformation in Air Versus Vacuum;205
17.7;14.7 Bio-Inspired Design of Insect-Sized Flapping Wings;206
17.8;14.8 Production of the Bio-Inspired Wings for an Insect-Sized MAV;208
17.9;14.9 Less Is More: Spinning Is More Efficient than Flapping an Insect Wing;209
17.10;Appendix 1 Suggested Web Sites for Ordering Micro-Components and Materials;211
17.11;Appendix 2 Tested Parameters;211
17.12;References;211
18;15 Springy Shells, Pliant Plates and Minimal Motors: Abstracting the Insect Thorax to Drive a Micro-Air Vehicle;213
18.1;15.1 Introduction;213
18.2;15.2 Some Requirements of a Small, Versatile Flying Machine: How Do Insects Manage?;214
18.2.1;15.2.1 Low Mass;214
18.2.2;15.2.2 Appropriate Kinematics;214
18.3;15.3 Biomimetic Possibilities;215
18.3.1;15.3.1 Kinematic Requirements;216
18.4;15.4 An Appropriate Thorax Design for Abstraction Higher Flies;216
18.5;15.5 Wing Biomimicry;221
18.6;15.6 Conclusion;222
18.7;References;222
19;16 Challenges for 100 Milligram Flapping Flight;224
19.1;16.1 Motivation and Background;224
19.2;16.2 Design of High-Frequency Flapping Mechanisms;225
19.2.1;16.2.1 Four Actuator Thorax;226
19.2.2;16.2.2 Single Actuator Thorax with Passive Rotation;226
19.3;16.3 Fabrication Using Smart Composite Manufacturing;227
19.4;16.4 Actuation and Power;227
19.5;16.5 Airfoils;229
19.6;16.6 Results;230
19.6.1;16.6.1 Dynamic Challenges for Active Control of Flap and Rotation;230
19.6.2;16.6.2 MFI Benchtop Lift Test;230
19.6.3;16.6.3 Flapping-Wing MAV with Passive Rotation;230
19.6.4;16.6.4 Benchtop Takeoff with Passive Rotation;232
19.7;16.7 Conclusion;232
19.8;References;233
20;17 The Limits of Turning Control in Flying Insects;235
20.1;17.1 Introduction;235
20.2;17.2 Free Flight Behavior and Yaw Turning;236
20.3;17.3 Forces and Moments During Turning Flight;238
20.3.1;17.3.1 Modeling Friction and Moment of Inertia;238
20.3.2;17.3.2 The Consequences of High Frictional Damping;240
20.4;17.4 Balancing Aerodynamic Forces During Maneuvering Flight;242
20.4.1;17.4.1 Forces and Velocities;242
20.4.2;17.4.2 Trade-Offs Between Locomotor Capacity and Control;243
20.4.2.1;17.4.2.1 The Trade-Off Between Lift, Thrust, and Lateral Forces;244
20.4.2.2;17.4.2.2 Collapse of Steering Envelope at Maximum Locomotor Performance;245
20.4.2.3;17.4.2.3 Significance of Muscle Precision and Response Time of Sensory Feedback;246
20.5;17.5 Synopsis;248
20.6;References;248
21;18 A Miniature Vehicle with Extended Aerial and Terrestrial Mobility;251
21.1;18.1 Introduction;251
21.1.1;18.1.1 Overview and Design Approach;252
21.1.1.1;18.1.1.1 Organization of Chapter;252
21.1.2;18.1.2 Micro-ground Vehicles;252
21.1.3;18.1.3 Micro-air Vehicles (MAVs);253
21.1.4;18.1.4 Multi-mode Mobility;253
21.2;18.2 Biologically Inspired Structures for Flying and Walking;254
21.2.1;18.2.1 Terrestrial Locomotion;254
21.2.2;18.2.2 Compliant Wings for Aerial Locomotion;255
21.3;18.3 MALV Design and Development;256
21.3.1;18.3.1 Methodology;256
21.3.1.1;18.3.1.1 Locomotion Mechanisms;256
21.3.1.2;18.3.1.2 Multi-modal Mobility Trade-Offs;257
21.3.1.3;18.3.1.3 Design Summary;258
21.3.2;18.3.2 MALV Design Implementation;258
21.3.3;18.3.3 Wing-Folding Mechanisms;261
21.3.3.1;18.3.3.1 Introduction;261
21.3.3.2;18.3.3.2 Mechanism Design;263
21.4;18.4 Results and Performance Testing;264
21.4.1;18.4.1 Vehicle Description;265
21.4.2;18.4.2 Multi-mode Locomotion;266
21.4.3;18.4.3 Transition Between Flight and Crawling;266
21.4.3.1;18.4.3.1 Air-to-Land Transition;267
21.4.3.2;18.3.3.2 Land-to-Air Transition;267
21.4.4;18.4.4 Sensor Capability and Integration;267
21.4.5;18.4.5 Flight Autonomy and (Video) Telemetry;268
21.4.5.1;18.4.5.1 Autopilot Tuning;269
21.4.5.2;18.4.5.2 Results;270
21.5;18.5 Conclusions;270
21.6;References;273
22;19 Towards a Self-Deploying and Gliding Robot;275
22.1;19.1 Introduction;275
22.2;19.2 Gliding in Robotics;276
22.2.1;19.2.1 Airframe, Sensing, and Actuation;277
22.2.2;19.2.2 Wing Folding;279
22.3;19.3 Jumping;282
22.4;19.4 System Integration;285
22.5;19.5 Conclusion;286
22.6;References;286
23;20 Solar-Powered Micro-air Vehicles and Challenges in Downscaling;289
23.1;20.1 Introduction;289
23.1.1;20.1.1 State of the Art;289
23.1.2;20.1.2 Objectives and Structure of this Chapter;289
23.2;20.2 Design Methodology;290
23.3;20.3 Methodology Application: The Sky-Sailor UAV;292
23.4;20.4 The Pros and Cons of Downscaling;293
23.4.1;20.4.1 Airframe;294
23.4.2;20.4.2 Low Reynolds Number Airfoil and Propeller;296
23.4.3;20.4.3 Actuators;296
23.4.4;20.4.4 Solar Cells;296
23.4.5;20.4.5 Maximum Power Point Tracker;298
23.4.6;20.4.6 Energy Storage;298
23.4.7;20.4.7 Control;298
23.5;20.5 Application Example on a Solar MAV;298
23.6;20.6 Conclusion;300
23.7;References;301
24;21 Technology and Fabrication of Ultralight Micro-Aerial Vehicles;302
24.1;21.1 Introduction;302
24.2;21.2 Platforms;303
24.2.1;21.2.1 Fixed-Wing Platforms;304
24.2.1.1;21.2.1.1 Reynolds Number and Polar Plots;304
24.2.1.2;21.2.1.2 Wing Profile;304
24.2.1.3;21.2.1.3 Wing Loading;306
24.2.1.4;21.2.1.4 Wing Construction;306
24.2.1.5;21.2.1.5 Power Requirements;307
24.2.2;21.2.2 Rotary-Wing Platforms;307
24.2.3;21.2.3 Flapping-Wing Platforms;308
24.3;21.3 Power and Energy Sources;309
24.3.1;21.3.1 Energy Sources;309
24.3.1.1;21.3.1.1 Batteries;310
24.3.1.2;21.3.1.2 Supercaps;311
24.3.1.3;21.3.1.3 Hydrogen Fuel Cells;311
24.3.2;21.3.2 Power Plants;311
24.3.2.1;21.3.2.1 Brushed DC Motors;311
24.3.2.2;21.3.2.2 Brushless DC Motors;312
24.3.2.3;21.3.2.3 Other Power Sources;312
24.3.3;21.3.3 Propellers;313
24.3.3.1;21.3.3.1 Propeller Sizing;313
24.3.3.2;21.3.3.2 Ducted Fans;314
24.4;21.4 Control Actuators;314
24.4.1;21.4.1 RC-Servos;315
24.4.2;21.4.2 Electromagnetic Actuators;315
24.4.3;21.4.3 Shape Memory Alloys;316
24.4.4;21.4.4 Electro-Active Polymers;316
24.5;21.5 Sensors and Processing Power;316
24.5.1;21.5.1 Obstacle Avoidance;316
24.6;21.6 Conclusion;317
24.7;References;317mehr
Kritik
From the reviews:"This book is a timely reminder of the beauty and agility of flying insects. ... Comprising of 21 Chapters, 50% written by engineers and 50% written by biologists in the field, this book brings together a collection of works rarely seen outside of a tight circle of like-minded individuals. ... The research compiled for this book represents the state-of-the-art in flying insect analysis, design and fabrication leading to an understanding of further developments in this area." (Stephen D. Prior, The Aeronautical Journal, December, 2010)mehr

Autor

Dario Floreano is the director of the Laboratory of Intelligent Systems at EPFL Lausanne. He has authored books on evolutionary robotics and bio-inspired artificial intelligence, and he has given invited talks on the topic at major conferences in robotics, computational intelligence, artificial life and natural computing. Jean-Christophe Zufferey is a scientist at EPFL Lausanne, specializing on research into aerial, bio-inspired and evolutionary robotics. He founded a company that specializes in educational robotics and indoor flyers, and he has gliding and flying pilot licenses. Mandyam V. Srinivasan heads the Visual and Sensory Neuroscience team at the Queensland Brain Institute. He studies the behaviour of small animals, in particular insects, and seeks to elucidate principles of flight control and navigation, and to explore the limits of the cognitive capacities of small brains. Charlie Ellington is Professor of Animal Mechanics at the University of Cambridge, and his interests are in the fields of biomechanics and comparative physiology, with a particular fascination for animal flight.