Introduction to AI robotics:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, MA
The MIT Press
[2019]
|
| Ausgabe: | Second edition |
| Schriftenreihe: | Intelligent robotics and autonomous agents
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturverzeichnis Seite 597-612 |
| Beschreibung: | xxiii, 620 Seiten Illustrationen, Diagramme |
| ISBN: | 9780262038485 |
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Datensatz im Suchindex
| DE-BY-862_location | 2000 |
|---|---|
| DE-BY-FWS_call_number | 2000/ZQ 6250 M978(2) |
| DE-BY-FWS_katkey | 751812 |
| DE-BY-FWS_media_number | 083000522269 083000523826 |
| _version_ | 1818201966044512256 |
| adam_text | Contents
I Framework for Thinking About AI and Robotics
1 What Are Intelligent Robots? 3
1 1 Overview 3
1 2 Definition: What Is an Intelligent Robot? 4
1 3 What Are the Components of a Robot? 7
1 4 Three Modalities: What Are the Kinds of Robots? 8
1 5 Motivation: Why Robots? 11
1 6 Seven Areas of AI: Why Intelligence? 13
1 7 Summary 15
1 8 Exercises 16
1 9 End Notes 17
2 A Brief History of AI Robotics 19
2 1 Overview 19
2 2 Robots as Tools, Agents, or Joint Cognitive Systems 20
2 3 World War II and the Nuclear Industry 21
2 4 Industrial Manipulators 24
2 5 Mobile Robots 29
2 6 Drones 35
2 7 The Move to Joint Cognitive Systems 36
2 8 Summary 37
2 9 Exercises 38
2 10 End Notes 38
3 Automation and Autonomy 41
3 1 Overview 41
3 2 The Four Sliders of Autonomous Capabilities 43
321 Plans: Generation versus Execution 44
322 Actions: Deterministic versus Non-deterministic 44
323 Models: Open- versus Closed-World 46
324 Knowledge Representation: Symbols versus Signals
3 3 Bounded Rationality 48
3 4 Impact of Automation and Autonomy 49
3 5 Impact on Programming Style 50
3 6 Impact on Hardware Design 50
3 7 Impact on Types of Functional Failures 52
371 Functional Failures 52
372 Impact on Types of Human Error 53
3 8 Trade-Spaces in Adding Autonomous Capabilities 55
3 9 Summary 57
3 10 Exercises 59
3 11 End Notes 61
Software Organization of Autonomy 63
4 1 Overview 64
4 2 The Three Types of Software Architectures 65
421 Types of Architectures 66
422 Architectures Reinforce Good Software
Engineering Principles 67
4 3 Canonical A1 Robotics Operational Architecture 68
431 Attributes for Describing Layers 68
432 The Reactive Layer 70
433 The Deliberative Layer 71
434 The Interactive Layer 74
435 Canonical Operational Architecture Diagram 75
4 4 Other Operational Architectures 75
441 Levels of Automation 76
442 Autonomous Control Levels (ACL) 78
443 Levels of Initiative 80
4 5 Five Subsystems in Systems Architectures 82
4 6 Three Systems Architecture Paradigms 85
461 Trait 1: Interaction Between Primitives 85
462 Trait 2: Sensing Route 87
463 Hierarchical Systems Architecture Paradigm 89
464 Reactive Systems Paradigm 91
465 Hybrid Deliberative/Reactive Systems Paradigm
4 7 Execution Approval and Task Execution 95
4 8 Summary 97
4 9 Exercises 100
4 10 End Notes 101
Contents
xi
5 Telesystems 103
5 1 Overview 104
5 2 Taskable Agency versus Remote Presence 105
5 3 The Seven Components of a Telesystem 105
5 4 Human Supervisory Control 108
541 Types of Supervisory Control 109
542 Human Supervisory Control for Telesystems 110
543 Manual Control 111
544 Traded Control 113
545 Shared Control 114
546 Guarded Motion 114
5 5 Human Factors 116
551 Cognitive Fatigue 117
552 Latency 118
553 Human: Robot Ratio 118
554 Human Out-of-the-Loop Control Problem 120
5 6 Guidelines for Determining if a Telesystem Is Suitable
for an Application 122
561 Examples of Telesystems 123
5 7 Summary 125
5 8 Exercises 126
5 9 End Notes 128
II Reactive Functionality 129
6 Behaviors 131
6 1 Overview 131
6 2 Motivation for Exploring Animal Behaviors 132
6 3 Agency and Marr s Computational Theory 134
6 4 Example of Computational Theory: Rana Computatrix 137
6 5 Animal Behaviors 141
651 Reflexive Behaviors 142
6 6 Schema Theory 143
661 Schemas as Objects 143
662 Behaviors and Schema Theory 144
663 S-R: Schema Notation 146
6 7 Summary 148
6 8 Exercises 150
6 9 End Notes 151
7 Perception and Behaviors 153
7 1 Overview 153
7 2 Action-Perception Cycle 155
7 3 Gibson: Ecological Approach 731 Optic Flow 158 156
732 Nonvisual Affordances 159
7 4 Two Perceptual Systems 161
7 5 Innate Releasing Mechanisms 162
751 Definition of Innate Releasing Mechanisms
752 Concurrent Behaviors 170
7 6 Two Functions of Perception 171
7 7 Example: Cockroach Hiding 771 Decomposition 171 171
772 Identifying Releasers 172
773 Implicit versus Explicit Sequencing 176
774 Perception 177
775 Architectural Considerations 178
7 8 Summary 178
7 9 Exercises 181
7 10 End Notes 182
8 Behavioral Coordination 185
8 1 Overview 185
8 2 Coordination Function 186
8 3 Cooperating Methods: Potential Fields 188
831 Visualizing Potential Fields 188
832 Magnitude Profiles 191
833 Potential Fields and Perception 194
834 Programming a Single Potential Field 194
835 Combination of Fields and Behaviors 196
836 Example Using One Behavior per Sensor 199
837 Advantages and Disadvantages 202
8 4 Competing Methods: Subsumption 204
841 Example 206
8 5 Sequences: Finite State Automata 213
851A Follow the Road FSA 213
852A Pick Up the Trash FSA 217
8 6 Sequences: Scripts 220
8 7 AI and Behavior Coordination 222
8 8 Summary 223
8 9 Exercises 224
8 10 End Notes 226
Contents
xiii
9 Locomotion 229
9 1 Overview 229
9 2 Mechanical Locomotion 230
921 Holonomic versus Nonholonomic 231
922 Steering 231
9 3 Biomimetic Locomotion 235
9 4 Legged Locomotion 238
941 Number of Leg Events 239
942 Balance 240
943 Gaits 243
944 Legs with Joints 243
9 5 Action Selection 245
9 6 Summary 246
9 7 Exercises 247
9 8 End Notes 249
10 Sensors and Sensing 251
10 1 Overview 252
10 2 Sensor and Sensing Model 253
10 2 1 Sensors: Active or Passive 254
10 2 2 Sensors: Types of Output and Usage 255
10 3 Odometry, Inertial Navigation System (INS) and Global
Positioning System (GPS) 255
10 4 Proximity Sensors 256
10 5 Computer Vision 258
10 5 1 Computer Vision Definition 258
10 5 2 Grayscale and Color Representation 259
10 5 3 Region Segmentation 264
10 5 4 Color Histogramming 267
10 6 Choosing Sensors and Sensing 269
10 6 1 Logical Sensors 269
10 6 2 Behavioral Sensor Fusion 271
10 6 3 Designing a Sensor Suite 274
10 7 Summary 278
10 8 Exercises 280
10 9 End Notes 283
11 Range Sensing 285
11 1 Overview 285
11 2 Stereo 288
11 3 Depth from X 293
11 4 Sonar or Ultrasonics 293
11 4 1 Light Stripers 300
11 4 2 Lidar 302
11 4 3 RGB-D Cameras 304
11 4 4 Point Clouds 304
11 5 Case Study: Hors d Oeuvres, Anyone!
11 6 Summary 315
11 7 Exercises 315
11 8 End Notes 317
Ill Deliberative Functionality 319
12 Deliberation 321
12 1 Overview 321
12 2 Strips 323
12 2 1 More Realistic Strips Example 326
12 2 2 Strips Summary 331
12 2 3 Revisiting the Closed-World Assumption and
the Frame Problem 332
12 3 Symbol Grounding Problem 333
12 4 Global World Models 335
12 4 1 Local Perceptual Spaces 335
12 4 2 Multi-level or Hierarchical World Models 336
12 4 3 Virtual Sensors 338
12 4 4 Global World Model and Deliberation 339
12 5 Nested Hierarchical Controller 339
12 6 RAPS and 3T 342
12 7 Fault Detection Identification and Recovery 346
12 8 Programming Considerations 347
12 9 Summary 348
12 10 Exercises 349
12 11 End Notes 351
13 Navigation 353
13 1 Overview 353
13 2 The Four Questions of Navigation 355
13 3 Spatial Memory 358
13 4 Types of Path Planning 359
13 5 Landmarks and Gateways 361
13 6 Relational Methods 364
13 6 1 Distinctive Places 365
13 6 2 Advantages and Disadvantages 368
13 7 Associative Methods 369
Contents
13 8 Case Study of Topological Navigation with a Hybrid Architecture
13 8 1 Topological Path Planning 370
13 8 2 Navigation Scripts 375
13 8 3 Lessons Learned 378
13 9 Discussion of Opportunities for AI 379
13 10 Summary 381
13 11 Exercises 382
13 12 End Notes 384
14 Metric Path Planning and Motion Planning 385
14 1 Overview 385
14 2 Four Situations Where Topological Navigation Is Not Sufficient
14 3 Configuration Space 389
14 3 1 Meadow Maps 391
14 3 2 Generalized Voronoi Graphs 393
14 3 3 Regular Grids 394
14 3 4 Quadtrees 395
14 4 Metric Path Planning 396
14 4 1 A* and Graph-Based Planners 396
14 4 2 Wavefront-Based Planners 402
14 5 Executing a Planned Path 402
14 5 1 Subgoal Obsession 402
14 5 2 Replanning 404
14 6 Motion Planning 407
14 7 Criteria for Evaluating Path and Motion Planners 410
14 8 Summary 411
14 9 Exercises 413
14 10 End Notes 415
15 Localization, Mapping, and Exploration 417
15 1 Overview 418
15 2 Localization 419
15 3 Feature-Based Localization 421
15 4 Iconic Localization 423
15 5 Static versus Dynamic Environments 424
15 6 Simultaneous Localization and Mapping 424
15 7 Terrain Identification and Mapping 426
15 7 1 Digital Terrain Elevation Maps 427
15 7 2 Terrain Identification 427
15 7 3 Stereophotogrammetry 428
15 8 Scale and Traversability 432
15 8 1 Scale 432
15 8 2 Traversability Attributes 434
XVI
Contents
15 9 Exploration 435
15 9 1 Reactive Exploration 435
15 9 2 Frontier-Based Exploration 436
15 9 3 Generalized Voronoi Graph Methods 437
15 10 Localization, Mapping, Exploration, and AI 439
15 11 Summary 441
15 12 Exercises 442
15 13 End Notes 443
16 Learning 445
16 1 Overview 446
16 2 Learning 447
16 3 Types of Learning by Example 449
16 4 Common Supervised Learning Algorithms 450
16 4 1 Induction 450
16 4 2 Support Vector Machines 452
16 4 3 Decision Trees 452
16 5 Common Unsupervised Learning Algorithms 454
16 5 1 Clustering 454
16 5 2 Artificial Neural Networks 455
16 6 Reinforcement Learning 460
16 6 1 Utility Functions 461
16 6 2 Q-leaming 461
16 6 3 Q-leaming Example 464
16 6 4 Q-leaming Discussion 468
16 7 Evolutionary Robotics and Genetic Algorithms 468
16 8 Learning and Architecture 473
16 9 Gaps and Opportunities 474
16 10 Summary 475
16 11 Exercises 476
16 12 End Notes 478
IV Interactive Functionality 481
17 MultiRobot Systems (MRS) 483
17 1 Overview 484
17 2 Four Opportunities and Seven Challenges 484
17 2 1 Four Advantages of MRS 485
17 2 2 Seven Challenges in MRS 486
17 3 Multirobot Systems and A1 487
17 4 Designing MRS for Tasks 490
17 4 1 Tune Expectations for a Task
490
Contents
xvii
17 4 2 Subject of Action 491
17 4 3 Movement 492
17 4 4 Dependency 492
17 5 Coordination Dimension of MRS Design 493
17 6 Systems Dimensions in Design 494
17 6 1 Communication 495
17 6 2 MRS Composition 496
17 6 3 Team Size 498
17 7 Five Most Common Occurrences of MRS 499
17 8 Operational Architectures for MRS 501
17 9 Task Allocation 503
17 10 Summary 504
17 11 Exercises 505
17 12 End Notes 508
18 Human-Robot Interaction 511
18 1 Overview 512
18 2 Taxonomy of Interaction 514
18 3 Contributions from HCI, Psychology, Communications 516
18 3 1 Human-Computer Interaction 516
18 3 2 Psychology 517
18 3 3 Communications 518
18 4 User Interfaces 518
18 4 1 Eight Golden Rules for User Interface Design 519
18 4 2 Situation Awareness 522
18 4 3 Multiple Users 525
18 5 Modeling Domains, Users, and Interactions 525
18 5 1 Motivating Example of Users and Interactions 526
18 5 2 Cognitive Task Analysis 528
18 5 3 Cognitive Work Analysis 529
18 6 Natural Language and Naturalistic User Interfaces 531
18 6 1 Natural Language Understanding 531
18 6 2 Semantics and Communication 533
18 6 3 Models of the Inner State of the Agent 534
18 6 4 Multi-modal Communication 535
18 7 Human-Robot Ratio 538
18 8 Trust 540
18 9 Testing and Metrics 542
18 9 1 Data Collection Methods 543
18 9 2 Metrics 545
18 10 Human-Robot Interaction and the Seven Areas
of Artificial Intelligence 546
18 11 Summary 547
18 12 Exercises 549
18 13 End Notes 552
V Design and the Ethics of Building
Intelligent Robots 555
19 Designing and Evaluating Autonomous Systems 557
19 1 Overview 557
19 2 Designing a Specific Autonomous Capability 559
19 2 1 Design Philosophy 559
19 2 2 Five Questions for Designing an Autonomous Robot
19 3 Case Study: Unmanned Ground Robotics Competition 562
19 4 Taxonomies and Metrics versus System Design 569
19 5 Holistic Evaluation of an Intelligent Robot 571
19 5 1 Failure Taxonomy 572
19 5 2 Four Types of Experiments 573
19 5 3 Data to Collect 575
19 6 Case Study: Concept Experimentation 578
19 7 Summary 581
19 8 Exercises 582
19 9 End Notes 583
20 Ethics 585
20 1 Overview 585
20 2 Types of Ethics 587
20 3 Categorizations of Ethical Agents 588
20 3 1 Moor s Four Categories 588
20 3 2 Categories of Morality 589
20 4 Programming Ethics 590
20 4 1 Approaches from Philosophy 590
20 4 2 Approaches from Robotics 591
20 5 Asimov s Three Laws of Robotics 591
20 5 1 Problems with the Three Laws 592
20 5 2 The Three Laws of Responsible Robotics 592
20 6 Artificial Intelligence and Implementing Ethics 593
20 7 Summary 594
20 8 Exercises 594
20 9 End Notes 595
Bibliography 597
|
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| discipline | Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
| edition | Second edition |
| format | Book |
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| id | DE-604.BV046226508 |
| illustrated | Illustrated |
| indexdate | 2024-12-12T04:01:56Z |
| institution | BVB |
| isbn | 9780262038485 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-031605074 |
| oclc_num | 1126545880 |
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| physical | xxiii, 620 Seiten Illustrationen, Diagramme |
| publishDate | 2019 |
| publishDateSearch | 2019 |
| publishDateSort | 2019 |
| publisher | The MIT Press |
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| series2 | Intelligent robotics and autonomous agents |
| spellingShingle | Murphy, Robin 1957- Introduction to AI robotics Robotics Artificial intelligence Roboter (DE-588)4050208-9 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd Robotik (DE-588)4261462-4 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)4050208-9 (DE-588)4033447-8 (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 | Robotics Artificial intelligence Roboter (DE-588)4050208-9 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd Robotik (DE-588)4261462-4 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Robotics Artificial intelligence Roboter Künstliche Intelligenz Robotik Maschinelles Lernen |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031605074&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT murphyrobin introductiontoairobotics |
Inhaltsverzeichnis
THWS Schweinfurt Zentralbibliothek Lesesaal
| Signatur: |
2000 ZQ 6250 M978(2) |
|---|---|
| Exemplar 1 | ausleihbar Checked out – Rückgabe bis: 29.09.2025 Vormerken |
| Exemplar 2 | ausleihbar Checked out – Rückgabe bis: 08.12.2025 Vormerken |