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Navigating Mobile Robots: Sensors and Techniques

14 years 9 months ago
Navigating Mobile Robots: Sensors and Techniques
It's a complete robotic navigation cookbook! "This book surveys the state of the art in sensors, systems, methods and technologies utilized by a mobile robot to determine its position in the environment. The many potential "solutions" are roughly categorized into two groups: relative and absolute position measurements. The first includes odometry and inertial navigation; the second comprises active beacons, artificial and natural landmark recognition, and model matching. The authors compare and analyze these different methods based on technical publications and on commercial product and patent information. Comparison is centered around the following criteria: accuracy of position and orientation measurements, equipment needed, cost, sampling rate, effective range, computational power required, processing needs, and other special features. No robotics hobbyist or professional should be without this extraordinarily comprehensive look at robot positioning."
J. Borenstein, H. R. Everett, and L. Feng
Added 19 Jul 2009
Updated 19 Jul 2009
Authors J. Borenstein, H. R. Everett, and L. Feng
 INTRODUCTION xi
Part I Sensors for Mobile Robot Positioning
Chapter 1 Sensors for Dead Reckoning 3
1.1 Optical Encoders 3
1.1.1 Incremental Optical Encoders 4
1.1.2 Absolute Optical Encoders 6
1.2 Doppler Sensors 7
1.2.1 Micro-Trak Trak-Star Ultrasonic Speed Sensor 8
1.2.2 Other Doppler-Effect Systems 9
1.3 Typical Mobility Configurations 9
1.3.1 Differential Drive 9
1.3.2 Tricycle Drive 11
1.3.3 Ackerman Steering 11
1.3.4 Synchro Drive 13
1.3.5 Omnidirectional Drive 15
1.3.6 Multi-Degree-of-Freedom Vehicles 16
1.3.7 MDOF Vehicle with Compliant Linkage 17
1.3.8 Tracked Vehicles 18
Chapter 2 Heading Sensors 21
2.1 Mechanical Gyroscopes 21
2.1.1 Space-Stable Gyroscopes 22
2.1.2 Gyrocompasses 23
2.1.3 Commercially Available Mechanical Gyroscopes 23
2.1.3.1 Futaba Model Helicopter Gyro 23
2.1.3.2 Gyration, Inc. 24
2.2 Optical Gyroscopes 24
2.2.1 Active Ring-Laser Gyros 26
2.2.2 Passive Ring Resonator Gyros 28
2.2.3 Open-Loop Interferometric Fiber Optic Gyros 29
2.2.4 Closed-Loop Interferometric Fiber Optic Gyros 32
2.2.5 Resonant Fiber-Optic Gyros 32
2.2.6 Commercially Available Optical Gyroscopes 33
2.2.6.1 The Andrew AUTOGYRO 33
2.2.6.2 Hitachi Cable Ltd. OFG-3 34
2.3 Geomagnetic Sensors 34
2.3.1 Mechanical Magnetic Compasses 35
2.3.2 Fluxgate Compasses 36
2.3.2.1 Zemco Fluxgate Compasses 42
2.3.2.2 Watson Gyrocompass 44
2.3.2.3 KVH Fluxgate Compasses 45
2.3.3 Hall-Effect Compasses 46
2.3.4 Magnetoresistive Compasses 48
2.3.4.1 Philips AMR Compass 48
2.3.5 Magnetoelastic Compasses 49
Chapter 3 Active Beacons 53
3.1 Navstar Global Positioning System (GPS) 53
3.2 Ground-Based RF Systems 59
3.2.1 Loran 59
3.2.2 Kaman Sciences Radio Frequency Navigation Grid 60
3.2.3 Precision Location Tracking and Telemetry System 61
3.2.4 Motorola Mini-Ranger Falcon 61
3.2.5 Harris Infogeometric System 62
Chapter 4 Sensors for Map-Based Positioning 65
4.1 Time-of-Flight Range Sensors 65
4.1.1 Ultrasonic TOF Systems 67
4.1.1.1 Massa Products Ultrasonic Ranging Module Subsystems 67
4.1.1.2 Polaroid Ultrasonic Ranging Modules 69
4.1.2 Laser-Based TOF Systems 71
4.1.2.1 Schwartz Electro-Optics Laser Rangefinders 71
4.1.2.2 RIEGL Laser Measurement Systems 77
4.1.2.3 RVSI Long Optical Ranging and Detection System 79
4.2 Phase-Shift Measurement 82
4.2.1 Odetics Scanning Laser Imaging System 85
4.2.2 ESP Optical Ranging System 86
4.2.3 Acuity Research AccuRange 3000 87
4.2.4 TRC Light Direction and Ranging System 89
4.2.5 Swiss Federal Institute of Technology's 3-D Imaging Scanner 90
4.2.6 Improving Lidar Performance 91
4.3 Frequency Modulation 93
4.3.1 Eaton VORAD Vehicle Detection and Driver Alert System 95
4.3.2 Safety First Systems Vehicular Obstacle Detection and Warning System 96
Part II Systems and Methods for Mobile Robot Positioning
Chapter 5 Odometry and Other Dead-Reckoning Methods 101
5.1 Systematic and Non-Systematic Odometry Errors 101
5.2 Measurement of Odometry Errors 103
5.2.1 Measurement of Systematic Odometry Errors 103
5.2.1.1 The Unidirectional Square-Path Test 103
5.2.1.2 The Bidirectional Square-Path Experiment 105
5.2.2 Measurement of Non-Systematic Errors 107
5.3 Reduction of Odometry Errors 108
5.3.1 Reduction of Systematic Odometry Errors 109
5.3.1.1 Auxiliary Wheels and Basic Encoder Trailer 109
5.3.1.2 The Basic Encoder Trailer 110
5.3.1.3 Systematic Calibration 110
5.3.2 Reducing Non-Systematic Odometry Errors 114
5.3.2.1 Mutual Referencing 114
5.3.2.2 Internal Position Error Correction 114
5.4 Inertial Navigation 116
5.4.1 Accelerometers 117
5.4.2 Gyros 117
5.4.2.1 Barshan and Durrant-Whyte 118
5.4.2.2 Komoriya and Oyama] 119
5.5 Summary 120
Chapter 6 Active Beacon Navigation Systems 123
6.1 Discussion on Triangulation Methods 124
6.1.1 Three-Point Triangulation 124
6.1.2 Triangulation with More Than Three Landmarks 125
6.2 Ultrasonic Transponder Trilateration 126
6.2.1 IS Robotics 2-D Location System 127
6.2.2 Tulane University 3-D Location System 127
6.3 Optical Positioning Systems 129
6.3.1 Cybermotion Docking Beacon 130
6.3.2 Hilare 131
6.3.3 NAMCO LASERNET 132
6.3.4 Denning Branch International Robotics LaserNav Position Sensor 133
6.3.5 TRC Beacon Navigation System 134
6.3.6 Siman Sensors & Intelligent Machines Ltd., ROBOSENSE 135
6.3.7 Imperial College Beacon Navigation System 136
6.3.8 MTI Research CONACTM 137
6.3.9 Lawnmower CALMAN 140
6.4 Summary 140
Chapter 7 Landmark Navigation 141
7.1 Natural Landmarks 142
7.2 Artificial Landmarks 143
7.2.1 Global Vision 144
7.3 Artificial Landmark Navigation Systems 144
7.3.1 MDARS Lateral-Post Sensor 145
7.3.2 Caterpillar Self Guided Vehicle 146
7.3.3 Komatsu Ltd, Z-Shaped Landmark 147
7.4 Line Navigation 148
7.4.1 Thermal Navigational Marker 149
7.4.2 Volatile Chemicals Navigational Marker 149
7.5 Summary 150
Chapter 8 Map-Based Positioning 153
8.1 Map-Building 154
8.1.1 Map-Building and Sensor-Fusion 155
8.1.2 Phenomenological vs. Geometric Representation, Engelson and McDermott 155
8.2 Map Matching 156
8.2.1 Schiele and Crowley 157
8.2.2 Hinkel and Knieriemen -- The Angle Histogram 158
8.2.3 Wei�, Wetzler, and Puttkamer -- More on the Angle Histogram 160
8.2.4 Siemens' Roamer 162
8.3 Geometric and Topological Maps 163
8.3.1 Geometric Maps for Navigation 164
8.3.1.1 Cox 165
8.3.1.2 Crowley 166
8.3.1.3 Adams and von Fl�e 169
8.3.2 Topological Maps for Navigation1 70
8.3.2.1 Taylor 170
8.3.2.2 Courtney and Jain 170
8.3.2.3 Kortenkamp and Weymouth 171
8.4 Summary 173
Appendix A: A Word on Kalman Filters 174
Appendix B: Unit Conversions and Abbreviations 175
Appendix C: Systems-at-a-Glance Tables 177
References 195
Subject Index 209
Author Index 219
Company Index 223
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