Autonomous Land Vehicles

✍ Scribed by Karsten Berns, Ewald von Puttkamer

• Publisher: Vieweg and Teubner
• Year: 2009
• Tongue: English
• Leaves: 292
• Category: Library

✦ Synopsis

The economic potential of autonomous mobile robots will increase tremendously during the next years. Service robots such as cleaning machines and inspection or assistance robots will bring us great support in our daily lives. This textbook provides an introduction to the methods of controlling these robotic systems. Starting from mobile robot kinematics, the reader receives a systematic overview of the basic problems as well as methods and algorithms used for solving them. Localization, object recognition, map building, navigation, and control architectures for autonomous vehicles will be discussed in detail. A survey of specific service robot applications is also included. This book is a useful introduction to mobile robotics for beginners as well as advanced students and engineers.

✦ Table of Contents

3834804215......Page 1
Preface......Page 5
Contents......Page 6
1.1 Autonomous mobile robots......Page 10
1.2 Applications of autonomous mobile robots......Page 13
1.3 Historical overview......Page 16
1.4 Book overview......Page 22
2.1 Basics......Page 24
2.2 Wheel kinematics......Page 28
2.2.1 Kinematics of a differential drive vehicle......Page 31
2.2.2 Kinematics of an omnidirectional vehicle......Page 32
2.2.3 Kinematics of a vehicle with Mecanum wheels......Page 34
2.2.4 Pose calculation based on velocities......Page 36
2.3.1 Differential drive......Page 37
2.3.2 Tricycle drive......Page 39
2.3.3 Ackermann steering......Page 40
2.3.4 Double Ackermann steering......Page 41
2.3.5 Synchro drive......Page 43
2.3.6 Omnidrive......Page 44
2.4 Applying mobile robot kinematics......Page 46
3 Sensors......Page 48
3.1.2 Bumper......Page 49
3.1.3 Force sensors......Page 50
3.2.1 Odometry sensors......Page 51
3.2.3 Inclinometers......Page 53
3.3.1 Acceleration sensors......Page 55
3.3.2 Turning rate sensors......Page 59
3.4 Distance sensors......Page 64
3.4.1 Infrared sensors......Page 65
3.4.2 Ultrasonic sensors......Page 67
3.4.3 Correlation of ultrasound signals......Page 69
3.4.4 Laser sensors......Page 72
3.5.3 Stereo-camera systems......Page 75
4.1 Pose calculation from odometry......Page 82
4.2 Inertial measurement units (IMU)......Page 85
4.2.1 Simplified inertial calculation......Page 87
4.2.2 Implementation example with heuristics for absolute orientationmeasurement......Page 89
4.3 Localization based on optical flow......Page 92
4.4.2 Line extraction......Page 95
4.5.3 Triangulation using landmarks......Page 99
4.5.4 Measuring distances to artificial landmarks......Page 103
4.5.5 Artificial active landmarks......Page 104
4.6 Global positioning system (GPS)......Page 108
4.7 Kalman filter......Page 109
4.7.1 General idea......Page 110
4.7.2 Guessing error......Page 111
4.7.3 Example application......Page 112
5 Mapping......Page 115
5.1.1 Line based metrical maps......Page 117
5.1.2 Plane based metrical maps......Page 122
5.1.3 Feature-based metrical maps......Page 128
5.2 Grid maps......Page 135
5.2.1 Occupancy grid maps......Page 136
5.3 Sector maps......Page 138
5.4 Topological maps......Page 143
5.4.1 Growing neural gas net......Page 146
5.5 Hybrid maps......Page 152
6.1 The general approach......Page 155
6.2 Merging local maps......Page 156
6.2.1 Correlation of laser scans......Page 157
6.2.2 Correlation of point clouds......Page 162
6.2.3 Loop closing......Page 167
6.3.1 An uncertainty model......Page 168
6.3.2 SLAM as Bayesian network......Page 169
6.3.3 The path estimator......Page 171
6.3.4 The landmark estimators......Page 172
6.3.5 Numeric computation of FastSLAM......Page 173
6.4 Exploration of the environment......Page 178
7.1.1 A*-algorithm......Page 182
7.1.3 Back tracking algorithm......Page 187
7.2.1 Path planning on geometric maps......Page 190
7.2.2 Navigation on a raster map......Page 202
7.2.3 Quadtree based path planning......Page 205
7.2.4 Area covering paths......Page 206
7.2.5 Exploration......Page 210
7.2.6 Obstacle avoidance......Page 212
7.2.7 Potential field method......Page 215
7.2.8 Basic abilities......Page 217
7.3 Path control......Page 227
8 Control Architectures......Page 231
8.1 The hierarchical task-oriented control architecture RCS......Page 233
8.2 Behavior-based control architectures......Page 236
8.2.1 The Subsumption Architecture......Page 238
8.2.2 Reuse and temporal sequences of behaviors......Page 240
8.3 The integrated behavior-based control architecture iB2C......Page 241
8.3.1 The basic behavior module......Page 242
8.3.2 Fusion behavior module......Page 245
8.3.3 Behavior interaction......Page 249
8.3.4 Behavior coordination......Page 250
8.3.5 Design guidelines......Page 252
8.3.6 Analysis of iB2C networks......Page 255
9 Software frameworks......Page 258
9.1 The Player Project......Page 259
9.2 Microsoft Robotics Developer Studio......Page 262
9.3 Orca......Page 266
9.4 MCA – Modular Controller Architecture......Page 270
9.5 Summary and comparison of robotic frameworks......Page 273
Bibliography......Page 276
G......Page 289
O......Page 290
W......Page 291