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Computational Principles of Mobile Robotics

ISBN: 9780521692120 | 0521692121
Edition: 2nd
Format: Paperback
Publisher: Cambridge University Press
Pub. Date: 7/26/2010

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SummaryTable of ContentsAuthor Biography
This textbook for advanced undergraduates and graduate students emphasizes computation and algorithms for a range of strategies for locomotion, sensing, and reasoning. It concentrates on wheeled and legged mobile robots but discusses a variety of other propulsion systems. This second edition presents advances in robotics and intelligent machines over the last ten years and includes additional mathematical background and an extensive list of sample problems.
New edition of an advanced undergraduate/graduate text, em... MORE
Acknowledgmentsp. xi
Perface to the Second Editionp. xiii
Overview and Motivationp. 1
From Mechanisms to Computationp. 4
Historical Contextp. 5
Biological Inspirationp. 11
Operational Regimesp. 11
Operational Modesp. 11
A Guide to This Bookp. 12
Further Readingp. 13
Problems... MOREp. 16
Fundamental Problemsp. 18
Path Planning for a Point Robotp. 19
Localization for a Point Robotp. 21
Sensing for a Point Robotp. 23
Mapping for a Point Robotp. 25
SLAM for a Point Robotp. 25
Looking Forwardp. 26
Further Readingp. 27
Problemsp. 27
Locomotion and Perceptionp. 29
Mobile Robot Hardwarep. 31
Locomotionp. 31
Off-Board Communicationp. 71
Processingp. 75
Further Readingp. 76
Problemsp. 77
Non-Visual Sensors and Algorithmsp. 82
Basic Conceptsp. 82
Contact Sensors: Bumpersp. 86
Inertial Sensorsp. 87
Infrared Sensorsp. 90
Sonarp. 91
Radarp. 98
Laser Rangefindersp. 98
Satellite-Based Positioningp. 100
Data Fusionp. 102
Biological Sensingp. 118
Further Readingp. 120
Problemsp. 121
Visual Sensors and Algorithmsp. 123
Visual Sensorsp. 124
Object Appearance and Shadingp. 131
Signals and Samplingp. 132
Image Features and Their Combinationp. 134
Obtaining Depthp. 149
Active Visionp. 155
Other Sensorsp. 158
Biological Visionp. 162
Further Readingp. 163
Problemsp. 164
Representation and Planningp. 165
Representing and Reasoning About Spacep. 167
Representing Spacep. 167
Representing the Robotp. 176
Path Planning for Mobile Robotsp. 179
Planning for Multiple Robotsp. 208
Biological Mappingp. 209
Further Readingp. 210
Problemsp. 210
System Controlp. 212
Horizontal Decompositionp. 213
Vertical Decompositionp. 217
Hybrid Control Architecturesp. 223
Middlewarep. 226
High-Level Controlp. 226
Alternative Control Formalismsp. 230
The Human-Robot Interfacep. 235
Mobile Robot Software Development as Experimentationp. 237
Standard Software Toolkitsp. 237
Further Readingp. 238
Problemsp. 239
Pose Maintenance and Localizationp. 240
Simple Landmark Measurementp. 241
Servo Controlp. 249
Recursive Filteringp. 250
Non-Geometric Methods: Perceptual Structurep. 260
Correlation-Based Localizationp. 267
Global Localizationp. 267
Biological Approaches to Localizationp. 273
Further Readingp. 274
Problemsp. 274
Mapping and Related Tasksp. 276
Sensorial Mapsp. 278
Geometric Mapsp. 279
Topological Mapsp. 287
Explorationp. 291
Further Readingp. 294
Problemsp. 294
Robot Collectivesp. 295
Categorizing Collectivesp. 296
Control Architecturesp. 296
Collective Communicationp. 299
Sensingp. 300
Planning for Actionp. 301
Formation Controlp. 302
Localizationp. 303
Mappingp. 304
Further Readingp. 305
Problemsp. 306
Robots in Practicep. 307
Delivery Robotsp. 307
Intelligent Vehiclesp. 309
Robots for Survey and Inspectionp. 314
Mining Automationp. 316
Space Roboticsp. 317
Autonomous Aircraftp. 319
Military Reconnaissancep. 320
Bomb/Mine Disposalp. 320
Underwater Inspectionp. 322
Agriculture/Forestryp. 323
Aids for the Disabledp. 325
Entertainmentp. 326
Domestic Robotsp. 327
Further Readingp. 327
Problemsp. 328
The Future of Mobile Roboticsp. 329
Locomotionp. 329
Sensorsp. 331
Controlp. 332
System Integrationp. 332
Standardizationp. 333
Future Directionsp. 333
Probability and Statisticsp. 335
Probabilityp. 335
Some Simple Statisticsp. 338
Further Readingp. 339
Problemsp. 339
Linear Systems, Matrices, and Filteringp. 341
Linear Algebrap. 341
Matrix Algebrap. 341
Signals and Systemsp. 343
Fourier Theoryp. 344
Sampling and the Nyquist Theoremp. 344
Further Readingp. 345
Problemsp. 345
Markov Modelsp. 346
Discrete Markov Processp. 346
Hidden Markov Modelsp. 348
Markov Decision Processp. 349
POMDPp. 350
Further Readingp. 351
Problemsp. 351
Bibliographyp. 353
Indexp. 381
Table of Contents provided by Ingram. All Rights Reserved.
Gregory Dudek is James McGill Professor of Computer Science and the Director of the School of Computer Science and of the Mobile Robotics Laboratory at McGill University. Michael Jenkin is a Professor of Computer Science and Engineering at York University. He has coedited eight books on human and machine vision.


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