Introduction to AI robotics:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass.
Bradford Book [u.a.]
2000
|
| Schriftenreihe: | Intelligent robots and autonomous agents
A Bradford book |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIX, 466 S. Ill., graph. Darst. |
| ISBN: | 0262133830 |
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Datensatz im Suchindex
| _version_ | 1804128489280897024 |
|---|---|
| adam_text | INTRODUCTION TO AI ROBOTICS ROBIN R. MURPHY A BRADFORD BOOK THE MIT
PRESS CAMBRIDGE, MASSACHUSETTS LONDON, ENGLAND BRIEF CONTENTS I ROBOTIC
PARADIGMS 1 1 FROM TELEOPERATION TO AUTONOMY 13 2 THE HIERARCHICAL
PARADIGM 41 3 BIOLOGICAL FOUNDATIONS OF THE REACTIVE PARADIGM 67 4 THE
REACTIVE PARADIGM 105 5 DESIGNING A REACTIVE IMPLEMENTATION 155 6 COMMON
SENSING TECHNIQUES FOR REACTIVE ROBOTS 195 7 TFEE HYBRID
DELIBERATIVE/REACTIVE PARADIGM 257 8 MULTI-AGENTS 293 II NAVIGATION 315
9 TOPOLOGICAL PATH PLANNING 325 10 METRIC PATH PLANNING 351 11
LOCALIZATION AND MAP MAKING 375 12 ON THE HORIZON 435 CONTENTS PREFACE
XVII I ROBOTIC PARADIGMS 1 1 FROM TELEOPERATION TO AUTONOMY 13 1.1
OVERVIEW 13 1.2 HOW CAN A MACHINE BE INTELLIGENT? 15 1.3 WHAT CAN ROBOTS
BE USED FOR? 16 1.3.1 SOCIAL IMPLICATIONS OF ROBOTICS 18 1.4 A BRIEF
HISTORY OF ROBOTICS 19 1.4.1 INDUSTRIAL MANIPULATORS 21 1.4.2 SPACE
ROBOTICS AND THE AI APPROACH 26 1.5 TELEOPERATION 28 1.5.1 TELEPRESENCE
32 1.5.2 SEMI-AUTONOMOUS CONTROL 33 1.6 THE SEVEN AREAS OF AI 34 1.7
SUMMARY 37 1.8 EXERCISES 37 1.9 END NOTES 39 2 THE HIERARCHICAL PARADIGM
41 2.1 OVERVIEW 41 2.2 ATTRIBUTES OF THE HIERARCHICAL PARADIGM 42 2.2.1
STRIPS 44 2.2.2 MORE REALISTIC STRIPS EXAMPLE 46 2.2.3 STRIPS SUMMARY 52
CONTENTS 2.3 CLOSED WORLD ASSUMPTION AND THE FRAME PROBLEM 53 2.4
REPRESENTATIVE ARCHITECTURES 54 2.4.1 NESTED HIERARCHICAL CONTROLLER 54
2.4.2 NIST RCS 57 2.4.3 EVALUATION OF HIERARCHICAL ARCHITECTURES 59 2.5
ADVANTAGES AND DISADVANTAGES 61 2.6 PROGRAMMING CONSIDERATIONS 62 , 2.7
SUMMARY 62 2.8 EXERCISES 63 2.9 END NOTES 64 BIOLOGICAL FOUNDATIONS OF
THE REACTIVE PARADIGM 67 3.1 OVERVIEW 67 3.1.1 WHY EXPLORE THE
BIOLOGICAL SCIENCES? 69 3.1.2 AGENCY AND COMPUTATIONAL THEORY 70 3.2
WHAT ARE ANIMAL BEHAVIORS? 73 3.2.1 REFLEXIVE BEHAVIORS 74 3.3
COORDINATION AND CONTROL OF BEHAVIORS 75 3.3.1 INNATE RELEASING
MECHANISMS 77 3.3.2 CONCURRENT BEHAVIORS 82 3.4 PERCEPTION IN BEHAVIORS
83 3.4.1 ACTION-PERCEPTION CYCLE 83 3.4.2 TWO FUNCTIONS OF PERCEPTION 85
3.4.3 GIBSON: ECOLOGICAL APPROACH 85 3.4.4 NEISSER: TWO PERCEPTUAL
SYSTEMS 90 3.5 SCHEMA THEORY 91 3.5.1 BEHAVIORS AND SCHEMA THEORY 92 3.6
PRINCIPLES AND ISSUES IN TRANSFERRING INSIGHTS TO ROBOTS 97 3.7 SUMMARY
99 3.8 EXERCISES 100 3.9 END NOTES 102 THE REACTIVE PARADIGM 105 4.1
OVERVIEW 105 4.2 ATTRIBUTES OF REACTIVE PARADIGM 108 4.2.1
CHARACTERISTICS AND CONNOTATIONS OF REACTIVE BEHAVIORS 110 4.2.2
ADVANTAGES OF PROGRAMMING BY BEHAVIOR 112 4.2.3 REPRESENTATIVE
ARCHITECTURES 113 CONTENTS 4.3 SUBSUMPTION ARCHITECTURE 113 4.3.1
EXAMPLE 115 4.3.2 SUBSUMPTION SUMMARY 121 4.4 POTENTIAL FIELDS
METHODOLOGIES 122 4.4.1 VISUALIZING POTENTIAL FIELDS 123 4.4.2 MAGNITUDE
PROFILES 126 4.4.3 POTENTIAL FIELDS AND PERCEPTION 128 4.4.4 PROGRAMMING
A SINGLE POTENTIAL FIELD 129 4.4.5 COMBINATION OF FIELDS AND BEHAVIORS
130 4.4.6 EXAMPLE USING ONE BEHAVIOR PER SENSOR 134 4.4.7 PFIELDS
COMPARED WITH SUBSUMPTION 136 4.4.8 ADVANTAGES AND DISADVANTAGES 145 4.5
EVALUATION OF REACTIVE ARCHITECTURES 147 4.6 SUMMARY 148 4.7 EXERCISES
149 4.8 END NOTES 152 DESIGNING A REACTIVE IMPLEMENTATION 155 5.1
OVERVIEW 155 5.2 BEHAVIORS AS OBJECTS IN OOP 157 5.2.1 EXAMPLE: A
PRIMITIVE MOVE-TO-GOAL BEHAVIOR 158 5.2.2 EXAMPLE: AN ABSTRACT
FOLLOW-CORRIDOR BEHAVIOR 160 5.2.3 WHERE DO RELEASERS GO IN OOP? 162 5.3
STEPS IN DESIGNING A REACTIVE BEHAVIORAL SYSTEM 163 5.4 CASE STUDY:
UNMANNED GROUND ROBOTICS COMPETITION 165 5.5 ASSEMBLAGES OF BEHAVIORS
173 5.5.1 FINITE STATE AUTOMATA 174 5.5.2 A PICK UP THE TRASH FSA 178
5.5.3 IMPLEMENTATION EXAMPLES 182 5.5.4 ABSTRACT BEHAVIORS 184 5.5.5
SCRIPTS 184 5.6 SUMMARY 187 5.7 EXERCISES 188 5.8 END NOTES 191 COMMON
SENSING TECHNIQUES FOR REACTIVE ROBOTS 195 6.1 OVERVIEW 196 6.1.1
LOGICAL SENSORS 197 6.2 BEHAVIORAL SENSOR FUSION 198 XII CONTENTS 6.3
DESIGNING A SENSOR SUITE 202 6.3.1 ATTRIBUTES OF A SENSOR 203 6.3.2
ATTRIBUTES OF A SENSOR SUITE 206 6.4 PROPRIOCEPTIVE SENSORS 207 6.4.1
INERTIAL NAVIGATION SYSTEM (INS) 208 6.4.2 GPS 208 6.5 PROXIMITY SENSORS
210 * 6.5.1 SONAR OR ULTRASONICS 210 6.5.2 INFRARED (IR) 216 , 6.5.3
BUMP AND FEELER SENSORS 217 6.6 COMPUTER VISION 218 6.6.1 CCD CAMERAS
219 6.6.2 GRAYSCALE AND COLOR REPRESENTATION 220 6.6.3 REGION
SEGMENTATION 226 6.6.4 COLOR HISTOGRAMMING 228 6.7 RANGE FROM VISION 231
6.7.1 STEREO CAMERA PAIRS 232 6.7.2 LIGHT STRIPERS 235 6.7.3 LASER
RANGING 239 6.7.4 TEXTURE 241 6.8 CASE STUDY: HORS D OEUVRES, ANYONE?
242 6.9 SUMMARY 250 6.10 EXERCISES 251 6.11 END NOTES 254 7 THE HYBRID
DELIBERATIVE/REACTIVE PARADIGM 257 7.1 OVERVIEW 257 7.2 ATTRIBUTES OF
THE HYBRID PARADIGM 259 7.2.1 CHARACTERISTICS AND CONNOTATION OF
REACTIVE BEHAVIORS IN HYBRIDS 261 7.2.2 CONNOTATIONS OF GLOBAL 262 7.3
ARCHITECTURAL ASPECTS 262 7.3.1 COMMON COMPONENTS OF HYBRID
ARCHITECTURES 263 7.3.2 STYLES OF HYBRID ARCHITECTURES 264 7.4
MANAGERIAL ARCHITECTURES 265 7.4.1 AUTONOMOUS ROBOT ARCHITECTURE (AURA)
265 7.4.2 SENSOR FUSION EFFECTS (SFX) 268 7.5 STATE-HIERARCHY
ARCHITECTURES 274 7.5.1 3-TIERED(3T) 274 CONTENTS 7.6 MODEL-ORIENTED
ARCHITECTURES 277 7.6.1 SAPHIRA 278 7.6.2 TASK CONTROL ARCHITECTURE
(TCA) 280 7.7 OTHER ROBOTS IN THE HYBRID PARADIGM 283 7.8 EVALUATION OF
HYBRID ARCHITECTURES 284 7.9 INTERLEAVING DELIBERATION AND REACTIVE
CONTROL 285 7.10 SUMMARY 288 7.11 EXERCISES 289 7.12 END NOTES 291 8
MULTI-AGENTS 293 8.1 OVERVIEW 293 8.2 HETEROGENEITY 296 8.2.1
HOMOGENEOUS TEAMS AND SWARMS 296 8.2.2 HETEROGENEOUS TEAMS 297 8.2.3
SOCIAL ENTROPY 300 8.3 CONTROL 301 8.4 COOPERATION 303 8.5 GOALS 304 8.6
EMERGENT SOCIAL BEHAVIOR 305 8.6.1 SOCIETAL RULES 305 8.6.2 MOTIVATION
307 8.7 SUMMARY 309 8.8 EXERCISES 310 8.9 END NOTES 312 II NAVIGATION
315 9 TOPOLOGICAL PATH PLANNING 325 9.1 OVERVIEW 325 9.2 LANDMARKS AND
GATEWAYS 326 9.3 RELATIONAL METHODS 328 9.3.1 DISTINCTIVE PLACES 329
9.3.2 ADVANTAGES AND DISADVANTAGES 331 9.4 ASSOCIATIVE METHODS 333 9.4.1
VISUAL HOMING 334 9.4.2 QUALNAV 335 XIV CONTENTS 9.5 CASE STUDY OF
TOPOLOGICAL NAVIGATION WITH A HYBRID ARCHITECTURE 338 9.5.1 PATH
PLANNING 339 9.5.2 NAVIGATION SCRIPTS 343 9.5.3 LESSONS LEARNED 346 9.6
SUMMARY 348 9.7 EXERCISES 348 * 9.8 END NOTES 350 10 METRIC PATH
PLANNING 351 10.1 OBJECTIVES AND OVERVIEW 351 10.2 CONFIGURATION SPACE
353 10.3 CSPACE REPRESENTATIONS 354 10.3.1 MEADOW MAPS 354 10.3.2
GENERALIZED VORONOI GRAPHS 357 10.3.3 REGULAR GRIDS 358 10.3.4 QUADTREES
359 10.4 GRAPH BASED PLANNERS 359 10.5 WAVEFRONT BASED PLANNERS 365 10.6
INTERLEAVING PATH PLANNING AND REACTIVE EXECUTION 367 10.7 SUMMARY 371
10.8 EXERCISES 372 10.9 END NOTES 374 11 LOCALIZATION AND MAP MAKING 375
11.1 OVERVIEW 375 11.2 SONAR SENSOR MODEL 378 11.3 BAYESIAN 380 11.3.1
CONDITIONAL PROBABILITIES 381 11.3.2 CONDITIONAL PROBABILITIES FOR
P(H S) 384 11.3.3 UPDATING WITH BAYES RULE 385 11.4 DEMPSTER-SHAFER
THEORY 386 11.4.1 SHAFER BELIEF FUNCTIONS 387 11.4.2 BELIEF FUNCTION FOR
SONAR 389 11.4.3 DEMPSTER S RULE OF COMBINATION 390 11.4.4 WEIGHT OF
CONFLICT METRIC 394 11.5 HIMM 395 11.5.1 HIMM SONAR MODEL AND UPDATING
RULE 395 11.5.2 GROWTH RATE OPERATOR 398 CONTENTS XV 11.6 COMPARISON OF
METHODS 403 11.6.1 EXAMPLE COMPUTATIONS 403 11.6.2 PERFORMANCE 411
11.6.3 ERRORS DUE TO OBSERVATIONS FROM STATIONARY ROBOT 412 11.6.4
TUNING 413 11.7 LOCALIZATION 415 11.7.1 CONTINUOUS LOCALIZATION AND
MAPPING 416 11.7.2 FEATURE-BASED LOCALIZATION 421 11.8 EXPLORATION 424
11.8.1 FRONTIER-BASED EXPLORATION 425 11.8.2 GENERALIZED VORONOI GRAPH
METHODS 427 11.9 SUMMARY 428 11.10 EXERCISES 431 11.11 END NOTES 434 12
ON THE HORIZON 435 12.1 OVERVIEW 435 12.2 SHAPE-SHIFTING AND LEGGED
PLATFORMS 438 12.3 APPLICATIONS AND EXPECTATIONS 442 12.4 SUMMARY 445
12.5 EXERCISES 445 12.6 END NOTES 447 BIBLIOGRAPHY 449 INDEX 459
|
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| id | DE-604.BV013676694 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T18:50:03Z |
| institution | BVB |
| isbn | 0262133830 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-009345019 |
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| physical | XIX, 466 S. Ill., graph. Darst. |
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| publisher | Bradford Book [u.a.] |
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| spelling | Murphy, Robin R. Verfasser aut Introduction to AI robotics Robin R. Murphy Cambridge, Mass. Bradford Book [u.a.] 2000 XIX, 466 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Intelligent robots and autonomous agents A Bradford book Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Roboter (DE-588)4050208-9 gnd rswk-swf Robotik (DE-588)4261462-4 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Roboter (DE-588)4050208-9 s Künstliche Intelligenz (DE-588)4033447-8 s DE-604 Robotik (DE-588)4261462-4 s Maschinelles Lernen (DE-588)4193754-5 s 1\p DE-604 HEBIS Datenaustausch Darmstadt application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009345019&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Murphy, Robin R. Introduction to AI robotics Künstliche Intelligenz (DE-588)4033447-8 gnd Roboter (DE-588)4050208-9 gnd Robotik (DE-588)4261462-4 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)4033447-8 (DE-588)4050208-9 (DE-588)4261462-4 (DE-588)4193754-5 |
| title | Introduction to AI robotics |
| title_auth | Introduction to AI robotics |
| title_exact_search | Introduction to AI robotics |
| title_full | Introduction to AI robotics Robin R. Murphy |
| title_fullStr | Introduction to AI robotics Robin R. Murphy |
| title_full_unstemmed | Introduction to AI robotics Robin R. Murphy |
| title_short | Introduction to AI robotics |
| title_sort | introduction to ai robotics |
| topic | Künstliche Intelligenz (DE-588)4033447-8 gnd Roboter (DE-588)4050208-9 gnd Robotik (DE-588)4261462-4 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Künstliche Intelligenz Roboter Robotik Maschinelles Lernen |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009345019&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT murphyrobinr introductiontoairobotics |