Flying Insects and Robots (eBook)
XII, 316 Seiten
Springer Berlin (Verlag)
978-3-540-89393-6 (ISBN)
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.
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.
Preface 5
Contents 7
Contributors 9
1 Experimental Approaches Toward a Functional Understanding of Insect Flight Control 13
1.1 Introduction 13
1.1.1 Chapter Overview 14
1.2 Low-Level Flight Control Biomechanics of Free Flight 14
1.2.1 Research Background 15
1.2.2 Experiments 15
1.2.2.1 Hovering Flight 15
1.2.2.2 Maneuvering 17
1.2.3 Conclusions 17
1.3 Intermediate-Level Flight Control Visuomotor Reflexes 18
1.3.1 Research Background 18
1.3.2 Experiments 18
1.3.2.1 System Analysis of Visual Flight Speed Control Using Virtual Reality Display Technology 19
1.3.3 Conclusions 19
1.4 High-Level Flight Control Landmark-Guided Goal Navigation 20
1.4.1 Research Background 20
1.4.2 Experiments 20
1.4.3 Conclusions 22
1.5 Closing Words 23
References 23
2 From Visual Guidance in Flying Insects to Autonomous Aerial Vehicles 26
2.1 Introduction 26
2.2 Landing on a Horizontal Surface 27
2.3 Terrain Following 29
2.4 Practical Problems with the Measurement of Optic Flow 30
2.5 A Mirror-Based Vision System for Terrain Following and Landing 30
2.6 Height Estimation and Obstacle Detection During Complex Motions 32
2.7 Hardware Realization and System Tests 33
2.8 Extracting Information on Range and Topography 36
2.9 Preliminary Flight Tests 37
2.10 Conclusions and Discussion 37
References 38
3 Optic Flow Based Autopilots: Speed Control and Obstacle Avoidance 40
3.1 Introduction 40
3.2 From the Fly EMDs to Electronic Optic Flow Sensors 41
3.3 An Explicit Control Scheme for Ground Avoidance 42
3.3.1 Avoiding the Ground by Sensing the Ventral Optic Flow 43
3.3.2 The ''Optic Flow Regulator'' 45
3.3.3 Micro-Helicopter (MH) with a Downward-Looking Optic Flow Sensing Eye 45
3.3.4 Insects' Versus the Seeing Helicopter's Behavioral Patterns 46
3.4 An Explicit Control Scheme for Speed Control and Lateral Obstacle Avoidance 48
3.4.1 Effects of Lateral OF on Wall Clearance and Forward Speed 48
3.4.2 New Robotic Demonstrator Based on a Hovercraft (HO) 48
3.4.3 The LORA III Autopilot: A Dual OF Regulator 50
3.4.3.1 Side Control System 50
3.4.3.2 Forward Control System 50
3.4.4 ''Operating Point'' of the Dual OF Regulator 51
3.4.5 Simulation Results: Flight Paths Along Straight or Tapered Corridors 52
3.4.5.1 Wall-Following Behavior Along a Straight Corridor 52
3.4.5.2 ''Centering Behavior'': A Particular Case of ''Wall-Following Behavior'' 53
3.4.5.3 Flight Pattern Along a Tapered Corridor 54
3.5 Conclusion 56
3.5.1 Is There a Pilot Onboard an Insect? 56
3.5.2 Potential Aeronautics and Aerospace Applications 57
References 58
4 Active Vision in Blowflies: Strategies and Mechanisms of Spatial Orientation 62
4.1 Virtuosic Flight Behaviour: Approaches to Unravel the Underlying Mechanisms 62
4.2 Active Vision: The Sensory and Motor Side of the Closed ActionPerception Cycle 63
4.3 Extracting Spatial Information from Actively Generated Optic Flow 66
4.4 A CyberFly: Performance of Experimentally Established Mechanisms Under Closed-Loop Conditions 68
4.5 Conclusions 70
References 70
5 Wide-Field Integration Methods for Visuomotor Control 73
5.1 Introduction 73
5.2 The Insect Visuomotor System 74
5.3 Wide-Field Integration of Optic Flow 75
5.4 Application to a Micro-helicopter 76
5.5 Summary 80
References 80
6 Optic Flow to Steer and Avoid Collisions in 3D 82
6.1 Introduction 82
6.2 Review of Optic Flow-Based Flying Robots 83
6.3 Optic Flow 85
6.4 Control Strategy 87
6.5 Application to a 10-g Indoor Microflyer 89
6.5.1 Platform 89
6.5.2 Control Strategy 91
6.5.3 Results 91
6.6 Conclusions and Outlook 92
References 93
7 Visual Homing in Insects and Robots 96
7.1 Homing in Insects 96
7.2 Probing the Content of Insect Location Memories 97
7.3 Modelling Homing: Computer Simulations and Robotics Experiments 101
7.4 Homing in Natural Environments 103
7.5 Acquisition and Use of Visual Representations 104
7.6 Outlook 106
References 107
8 Motion Detection Chips for Robotic Platforms 110
8.1 Introduction 110
8.2 Algorithms for aVLSI Motion Detection Chips and Their Implementations 111
8.2.1 Gradient-Based Intensity Algorithm 113
8.2.2 Intensity-Based Correlation 115
8.2.3 Token-Based Correlation 115
8.2.4 Time-of-Travel 116
8.3 Promising Motion Chip Architectures 118
8.4 Summary 120
References 121
9 Insect-Inspired Odometry by Optic Flow Recorded with Optical Mouse Chips 124
9.1 Introduction 124
9.2 Hardware Implementations 125
9.3 Calibration 125
9.3.1 Head A 126
9.3.2 Head B 126
9.4 Odometry 127
9.4.1 Head A 128
9.4.2 Head B 129
9.4.3 Fast Estimates 129
9.5 Tests 129
9.5.1 Head A 130
9.5.2 Head B 130
9.5.2.1 Test for the Orientation and Size of the Estimated Rotation 130
9.5.2.2 Outdoor Test of T- and Distribution 131
9.5.2.3 Test for Evaluations of the Relative Nearness 132
9.6 Discussion 132
References 134
10 Microoptical Artificial Compound Eyes 136
10.1 Introduction 136
10.2 Miniaturization of Imaging Systems 137
10.3 The Compound Eyes of Insects 138
10.3.1 Apposition Compound Eyes 139
10.3.2 Superposition Compound Eyes 140
10.4 Insect-Inspired Imaging Systems 140
10.4.1 Artificial Apposition Compound Eyes 141
10.4.1.1 Prototype Demonstration 142
10.4.1.2 Increased Sensitivity with Artificial Neural Superposition 144
10.4.2 Artificial Superposition Compound Eyes 146
10.4.3 Fabrication of Artificial Compound Eye Optics 148
10.4.4 Future Challenges 149
References 150
11 Flexible Wings and Fluid0Structure Interactions for Micro-Air Vehicles 152
11.1 Introduction 152
11.2 Parameter Space and Scaling Laws 155
11.3 Fixed Membrane Wing MAVs 157
11.4 Aeroelasticity of Flapping (Plunging) Wings 161
11.5 Summary and Concluding Remarks 164
References 165
12 Flow Control Using Flapping Wings for an Efficient Low-Speed Micro-Air Vehicle 167
12.1 Introduction 167
12.2 Flapping Airfoil Aerodynamics 168
12.3 Effect of Viscosity on Flapping Airfoil Aerodynamics 170
12.4 The Bird Wing A Fully Integrated Lift/Propulsion/Control System 172
12.5 The Oscillating Airfoil A Two-Dimensional Propeller 172
12.6 Conceptual Design Considerations for a Flapping-Wing MAV 173
12.7 Summary and Outlook 176
References 177
13 A Passively Stable Hovering Flapping Micro-Air Vehicle 178
13.1 Introduction 178
13.2 Aerodynamics of Flapping Flight 179
13.2.1 Passive Wing Pitching 180
13.3 Machine Design 180
13.3.1 Design Improvements 184
13.4 Passive Stability 185
13.5 Performance Results 188
13.5.1 Future Design Changes 189
13.6 Conclusion 190
References 190
14 The Scalable Design of Flapping Micro-Air Vehicles Inspired by Insect Flight 192
14.1 Introduction 192
14.2 The Scalable Wing Aerodynamics of Hovering Insects 193
14.3 Design Approach: Scale a Flapping MAV That Works Down to Smaller Sizes 194
14.4 DelFly: A Flapping MAV That Works 194
14.5 DelFly II: Improved Design 199
14.6 DelFly II: Aerodynamic Analyses 199
14.6.1 DelFly Models Used for Aerodynamic Measurements 202
14.6.2 Lift as a Function of Flap Frequency at a Constant Flap Angle of 36 203
14.6.3 Lift and Power as a Function of Flap Angle at a Flap Frequency of 14 Hz 204
14.6.4 Power Requirement and Wing Deformation in Air Versus Vacuum 205
14.7 Bio-Inspired Design of Insect-Sized Flapping Wings 206
14.8 Production of the Bio-Inspired Wings for an Insect-Sized MAV 208
14.9 Less Is More: Spinning Is More Efficient than Flapping an Insect Wing 209
Appendix 1 Suggested Web Sites for Ordering Micro-Components and Materials 211
Appendix 2 Tested Parameters 211
References 211
15 Springy Shells, Pliant Plates and Minimal Motors: Abstracting the Insect Thorax to Drive a Micro-Air Vehicle 213
15.1 Introduction 213
15.2 Some Requirements of a Small, Versatile Flying Machine: How Do Insects Manage? 214
15.2.1 Low Mass 214
15.2.2 Appropriate Kinematics 214
15.3 Biomimetic Possibilities 215
15.3.1 Kinematic Requirements 216
15.4 An Appropriate Thorax Design for Abstraction Higher Flies 216
15.5 Wing Biomimicry 221
15.6 Conclusion 222
References 222
16 Challenges for 100 Milligram Flapping Flight 224
16.1 Motivation and Background 224
16.2 Design of High-Frequency Flapping Mechanisms 225
16.2.1 Four Actuator Thorax 226
16.2.2 Single Actuator Thorax with Passive Rotation 226
16.3 Fabrication Using Smart Composite Manufacturing 227
16.4 Actuation and Power 227
16.5 Airfoils 229
16.6 Results 230
16.6.1 Dynamic Challenges for Active Control of Flap and Rotation 230
16.6.2 MFI Benchtop Lift Test 230
16.6.3 Flapping-Wing MAV with Passive Rotation 230
16.6.4 Benchtop Takeoff with Passive Rotation 232
16.7 Conclusion 232
References 233
17 The Limits of Turning Control in Flying Insects 235
17.1 Introduction 235
17.2 Free Flight Behavior and Yaw Turning 236
17.3 Forces and Moments During Turning Flight 238
17.3.1 Modeling Friction and Moment of Inertia 238
17.3.2 The Consequences of High Frictional Damping 240
17.4 Balancing Aerodynamic Forces During Maneuvering Flight 242
17.4.1 Forces and Velocities 242
17.4.2 Trade-Offs Between Locomotor Capacity and Control 243
17.4.2.1 The Trade-Off Between Lift, Thrust, and Lateral Forces 244
17.4.2.2 Collapse of Steering Envelope at Maximum Locomotor Performance 245
17.4.2.3 Significance of Muscle Precision and Response Time of Sensory Feedback 246
17.5 Synopsis 248
References 248
18 A Miniature Vehicle with Extended Aerial and Terrestrial Mobility 251
18.1 Introduction 251
18.1.1 Overview and Design Approach 252
18.1.1.1 Organization of Chapter 252
18.1.2 Micro-ground Vehicles 252
18.1.3 Micro-air Vehicles (MAVs) 253
18.1.4 Multi-mode Mobility 253
18.2 Biologically Inspired Structures for Flying and Walking 254
18.2.1 Terrestrial Locomotion 254
18.2.2 Compliant Wings for Aerial Locomotion 255
18.3 MALV Design and Development 256
18.3.1 Methodology 256
18.3.1.1 Locomotion Mechanisms 256
18.3.1.2 Multi-modal Mobility Trade-Offs 257
18.3.1.3 Design Summary 258
18.3.2 MALV Design Implementation 258
18.3.3 Wing-Folding Mechanisms 261
18.3.3.1 Introduction 261
18.3.3.2 Mechanism Design 263
18.4 Results and Performance Testing 264
18.4.1 Vehicle Description 265
18.4.2 Multi-mode Locomotion 266
18.4.3 Transition Between Flight and Crawling 266
18.4.3.1 Air-to-Land Transition 267
18.3.3.2 Land-to-Air Transition 267
18.4.4 Sensor Capability and Integration 267
18.4.5 Flight Autonomy and (Video) Telemetry 268
18.4.5.1 Autopilot Tuning 269
18.4.5.2 Results 270
18.5 Conclusions 270
References 273
19 Towards a Self-Deploying and Gliding Robot 275
19.1 Introduction 275
19.2 Gliding in Robotics 276
19.2.1 Airframe, Sensing, and Actuation 277
19.2.2 Wing Folding 279
19.3 Jumping 282
19.4 System Integration 285
19.5 Conclusion 286
References 286
20 Solar-Powered Micro-air Vehicles and Challenges in Downscaling 289
20.1 Introduction 289
20.1.1 State of the Art 289
20.1.2 Objectives and Structure of this Chapter 289
20.2 Design Methodology 290
20.3 Methodology Application: The Sky-Sailor UAV 292
20.4 The Pros and Cons of Downscaling 293
20.4.1 Airframe 294
20.4.2 Low Reynolds Number Airfoil and Propeller 296
20.4.3 Actuators 296
20.4.4 Solar Cells 296
20.4.5 Maximum Power Point Tracker 298
20.4.6 Energy Storage 298
20.4.7 Control 298
20.5 Application Example on a Solar MAV 298
20.6 Conclusion 300
References 301
21 Technology and Fabrication of Ultralight Micro-Aerial Vehicles 302
21.1 Introduction 302
21.2 Platforms 303
21.2.1 Fixed-Wing Platforms 304
21.2.1.1 Reynolds Number and Polar Plots 304
21.2.1.2 Wing Profile 304
21.2.1.3 Wing Loading 306
21.2.1.4 Wing Construction 306
21.2.1.5 Power Requirements 307
21.2.2 Rotary-Wing Platforms 307
21.2.3 Flapping-Wing Platforms 308
21.3 Power and Energy Sources 309
21.3.1 Energy Sources 309
21.3.1.1 Batteries 310
21.3.1.2 Supercaps 311
21.3.1.3 Hydrogen Fuel Cells 311
21.3.2 Power Plants 311
21.3.2.1 Brushed DC Motors 311
21.3.2.2 Brushless DC Motors 312
21.3.2.3 Other Power Sources 312
21.3.3 Propellers 313
21.3.3.1 Propeller Sizing 313
21.3.3.2 Ducted Fans 314
21.4 Control Actuators 314
21.4.1 RC-Servos 315
21.4.2 Electromagnetic Actuators 315
21.4.3 Shape Memory Alloys 316
21.4.4 Electro-Active Polymers 316
21.5 Sensors and Processing Power 316
21.5.1 Obstacle Avoidance 316
21.6 Conclusion 317
References 317
Erscheint lt. Verlag | 23.10.2009 |
---|---|
Zusatzinfo | XII, 316 p. |
Verlagsort | Berlin |
Sprache | englisch |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Technik ► Elektrotechnik / Energietechnik | |
Technik ► Luft- / Raumfahrttechnik | |
Schlagworte | aerodynamics • Autonomous flying systems • Bioinspired design • Bioinspired systems • control engineering • Energy harvesting • Entomology • Ethology • Hybrid locomotion • Insect flight • Insectoids • Insects • Micro air vehicles • Microgliders • Micromac • Micromachines • motion detection • Neurophysiology • robots • Visual homing • Zoology |
ISBN-10 | 3-540-89393-8 / 3540893938 |
ISBN-13 | 978-3-540-89393-6 / 9783540893936 |
Haben Sie eine Frage zum Produkt? |
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