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E-raamat: Bio-inspired Flying Robots: Experimental Synthesis of Autonomous Indoor Flyers

(Laboratory of Intelligent Systems, Swiss Federal Institute of Technology, Switzerland)
  • Formaat: 250 pages
  • Ilmumisaeg: 24-Apr-2008
  • Kirjastus: CRC Press Inc
  • ISBN-13: 9781439808115
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  • Formaat: 250 pages
  • Ilmumisaeg: 24-Apr-2008
  • Kirjastus: CRC Press Inc
  • ISBN-13: 9781439808115
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This book demonstrates how bio-inspiration can lead to fully autonomous flying robots without relying on external aids. Most existing aerial robots fly in open skies, far from obstacles, and rely on external beacons, mainly GPS, to localise and navigate. However, these robots are not able to fly at low altitude or in confined environments, and yet this poses absolutely no difficulty to insects. Indeed, flying insects display efficient flight control capabilities in complex environments despite their limited weight and relatively tiny brain size.



From sensor suite to control strategies, the literature on flying insects is reviewed from an engineering perspective in order to extract useful principles that are then applied to the synthesis of artificial indoor flyers. Artificial evolution is also utilised to search for alternative control systems and behaviors that match the constraints of small flying robots. Specifically, the basic sensory modalities of insects, vision, gyroscopes and airflow sense, are applied to develop navigation controllers for indoor flying robots. These robots are capable of mapping sensor information onto actuator commands in real time to maintain altitude, stabilize the course and avoid obstacles. The most prominent result of this novel approach is a 10-gram microflyer capable of fully autonomous operation in an office-sized room using fly-inspired vision, inertial and airspeed sensors.



This book is intended for all those interested in autonomous robotics, in academia and industry.
Preface vii
Foreword ix
Introduction
1(10)
What's Wrong with Flying Robots?
1(2)
Flying Insects Don't Use GPS
3(3)
Proposed Approach
6(3)
Book Organisation
9(2)
Related Work
11(20)
Micromechanical Flying Devices
12(5)
Rotor-based Devices
12(1)
Flapping-wing Devices
13(4)
Bio-inspired Vision-based Robots
17(10)
Wheeled Robots
18(3)
Aerial Robots
21(6)
Evolution of Vision-based Navigation
27(3)
Conclusion
30(1)
Flying Insects
31(30)
Which Flying Insects?
31(2)
Sensor Suite for Flight Control
33(7)
Vision
34(3)
Vestibular Sense
37(2)
Airflow Sensing and Other Mechanosensors
39(1)
Information Processing
40(12)
Optic Lobes
41(1)
Local Optic-flow Detection
42(4)
Analysis of Optic-flow Fields
46(6)
In-Flight Behaviours
52(6)
Attitude Control
52(2)
Course (and Gaze) Stabilisation
54(1)
Collision Avoidance
55(2)
Altitude Control
57(1)
Conclusion
58(3)
Robotic Platforms
61(34)
Platforms
61(15)
Miniature Wheeled Robot
62(1)
Blimp
63(3)
Indoor Airplanes
66(10)
Comparative Summary of Robotic Platforms
76(1)
Embedded Electronics
76(10)
Microcontroller Boards
76(3)
Sensors
79(5)
Communication
84(2)
Software Tools
86(3)
Robot Interface
86(1)
Robot Simulator
87(2)
Test Arenas
89(2)
Conclusion
91(4)
Optic Flow
95(20)
What is Optic Flow?
96(6)
Motion Field and Optic Flow
96(1)
Formal Description and Properties
97(4)
Motion Parallax
101(1)
Optic Flow Detection
102(12)
Issues with Elementary Motion Detectors
102(1)
Gradient-based Methods
103(3)
Simplified Image Interpolation Algorithm
106(1)
Algorithm Assessment
107(3)
Implementation Issues
110(4)
Conclusion
114(1)
Optic-flow-based Control Strategies
115(34)
Steering Control
116(17)
Analysis of Frontal Optic Flow Patterns
116(6)
Control Strategy
122(3)
Results on Wheels
125(3)
Results in the Air
128(4)
Discussion
132(1)
Altitude Control
133(5)
Analysis of Ventral Optic Flow Patterns
133(2)
Control Strategy
135(1)
Results on Wheels
136(1)
Discussion
137(1)
3D Collision Avoidance
138(7)
Optic Flow Detectors as Proximity Sensors
139(1)
Control Strategy
140(1)
Results in the Air
141(2)
Discussion
143(2)
Conclusion
145(4)
Evolved Control Strategies
149(30)
Method
150(8)
Rationale
150(2)
Evolutionary Process
152(2)
Neural Controller
154(3)
Fitness Function
157(1)
Experiments on Wheels
158(9)
Raw Vision versus Optic Flow
159(5)
Coping with Stuck Situations
164(3)
Experiments in the Air
167(8)
Evolution in Simulation
168(4)
Transfer to Reality
172(3)
Conclusion
175(4)
Concluding Remarks
179(6)
What's next?
180(2)
Potential Applications
182(3)
Bibliography 185(18)
Index 203