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Introduction to AI Robotics R. Murphy (MIT Press 2000)

1 Introduction to AI Robotics Robin Murphy 1 What are Robots? • Objectives – Define Intelligent Robot Definition – Be able to list the four m odalities of aut

Robin R. Murphy

Robin R. Murphy An Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents) Publisher: A Bradford Book; 1st edition (November 13, 2000)

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Unifying Artificial Intelligence Robotics: An Undergraduate Textbook Introduction to AI Robotics. Robin R. Murphy. MIT Press/Bradford Books (2000).

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Contents

Robin R Murphy Introduction to AI Robotics ISBN-81-203-2458-7 PHI Publication. 3. Robert J. Schilling, Fundamentals of Robotics Analysis and Control,

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Unifying Artificial Intelligence Robotics: An Undergraduate Textbook. Introduction to AI Robotics. Robin R. Murphy. MIT Press/Bradford Books (2000). Hardcover,.

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Introduction to AI Robotics,. Robin R. Murphy, 2000. Strategic Negotiation in Multiagent Environments,. Sarit Kraus, 2001. Mechanics of Robotic Manipulation, .

Part II Chapter 9: Topological Path Planning Navigation Spatial

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Junior/Senior level Introduction to Robotics course from a computer science perspective [23] Robin R. Murphy, Introduction to AI Robotics, MIT Press, 2000.

Intelligent Autonomous Robotics

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Robin R. Murphy, University of South Florida. ARTIFICIAL AI for robotics as being harder to teach than, say, Java. Press, 2000), and my An Introduction to AI.

Murphy - CRA

Bart Everett, and the University of South Florida led by Robin Murphy. Center personnel Dr. Robin R. Murphy Associate Professor, Department of. Computer field, including the textbook Introduction to AI Robotics (MIT Press). Her preferred?

Use of Dempster-Shafer Conflict Metric to Adapt Sensor Allocatio

Jennifer Carlson and Robin R. Murphy. University (Carlson & Murphy 2005) indicated that the Gambino indi- cator may R. 2000. Introduction to AI Robotics .

principles and experiences in using legos to teach behavioral ro

2 Robin R. Murphy, Dept. of Computer Science and Engineering, University of South Florida, Tampa, with the instructor's guide to Introduction to AI Robotics.

I N T R O D U C T I O N T O AI ROBOTICS ROBIN R. MURPHY

• Page 2 and 3: Introduction to AI Robotics
• Page 4 and 5: Introduction to AI Robotics Robin R
• Page 6: To Kevin ..andCarlyleRamsey,Monroe
• Page 10 and 11: Contents Preface xvii I Robotic Par
• Page 12 and 13: Contents xi 4.3 Subsumption Archite
• Page 14 and 15: Contents xiii 7.6 Model-Oriented Ar
• Page 16: Contents xv 11.6 Comparison of Meth
• Page 19 and 20: xviii Preface a head start on a pro
• Page 22 and 23: P ART I Robotic Paradigms
• Page 24 and 25: INTELLIGENT ROBOT Part I 3 word “
• Page 26 and 27: PARADIGM ROBOTIC PARADIGMS Part I 5
• Page 28 and 29: Part I 7 SENSE PLAN ACT a. PLAN SEN
• Page 30 and 31: HYBRID DELIBERA- TIVE/REACTIVE PARA
• Page 32 and 33: MODULARITY NICHE TARGETABILITY PORT
• Page 34 and 35: 1 From Teleoperation To Autonomy Ch
• Page 36 and 37: 1.2 How Can a Machine Be Intelligen
• Page 38 and 39: 1.3 What Can Robots Be Used For? 17
• Page 40 and 41: 1.4 A Brief History of Robotics 19
• Page 42 and 43: 1.4 A Brief History of Robotics 21
• Page 44 and 45: FEEDBACK 1.4 A Brief History of Rob
• Page 46 and 47: BLACK FACTORY 1.4 A Brief History o
• Page 48 and 49: 1.4 A Brief History of Robotics 27
• Page 50 and 51: 1.5 Teleoperation 29 LOCAL Display
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  1.5 Teleoperation 31 because of the

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  TELEPRESENCE VIRTUAL REALITY 1.5 Te

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  1.6 The Seven Areas of AI 35 how th

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  1.7 Summary 37 1.7 Summary AI robot

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  1.9 End Notes 39 Exercise 1.15 [Adv

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  2 The Hierarchical Paradigm Chapter

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  WORLD MODEL APRIORI 2.2 Attributes

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  DIFFERENCE TABLE PRECONDITIONS 2.2

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  AXIOMS PREDICATES 2.2 Attributes of

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  2.2 Attributes of the Hierarchical

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  2.2 Attributes of the Hierarchical

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  2.3 Closed World Assumption and the

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  2.4 Representative Architectures 55

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  2.4 Representative Architectures 57

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  NASREM 2.4 Representative Architect

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  2.5 Advantages and Disadvantages 61

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  2.8 Exercises 63 chitecture will su

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  2.9 End Notes 65 Robot name trivia.

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  68 3 Biological Foundations of the

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  70 3 Biological Foundations of the

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  72 3 Biological Foundations of the

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  74 3 Biological Foundations of the

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  76 3 Biological Foundations of the

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  78 3 Biological Foundations of the

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  80 3 Biological Foundations of the

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  82 3 Biological Foundations of the

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  84 3 Biological Foundations of the

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  86 3 Biological Foundations of the

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  88 3 Biological Foundations of the

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  90 3 Biological Foundations of the

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  92 3 Biological Foundations of the

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  94 3 Biological Foundations of the

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  96 3 Biological Foundations of the

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  98 3 Biological Foundations of the

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  100 3 Biological Foundations of the

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  102 3 Biological Foundations of the

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  4 The Reactive Paradigm Chapter Obj

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  4.1 Overview 107 sensors build maps

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  4.2 Attributes of Reactive Paradigm

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  SITUATED AGENT ECOLOGICAL ROBOTICS

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  RULE ENCODING 4.3 Subsumption Archi

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  4.3 Subsumption Architecture 115 mo

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  4.3 Subsumption Architecture 117 Fi

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  INHIBITION SUPPRESSION 4.3 Subsumpt

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  4.3 Subsumption Architecture 121 SO

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  4.4 Potential Fields Methodologies

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  PERPENDICULAR FIELD ATTRACTIVE FIEL

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  4.4 Potential Fields Methodologies

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  4.4 Potential Fields Methodologies

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  4.4 Potential Fields Methodologies

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  4.4 Potential Fields Methodologies

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  4.4 Potential Fields Methodologies

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  4.4 Potential Fields Methodologies

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  4.4 Potential Fields Methodologies

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  4.4 Potential Fields Methodologies

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  4.4 Potential Fields Methodologies

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  4.4 Potential Fields Methodologies

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  4.5 Evaluation of Reactive Architec

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  4.7 Exercises 149 ior is emergent.

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  4.7 Exercises 151 Exercise 4.14 How

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  4.8 End Notes 153 mobile robot in b

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  156 5 Designing a Reactive Implemen

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  158 5 Designing a Reactive Implemen

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  160 5 Designing a Reactive Implemen

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  162 5 Designing a Reactive Implemen

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  164 5 Designing a Reactive Implemen

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  166 5 Designing a Reactive Implemen

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  168 5 Designing a Reactive Implemen

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  170 5 Designing a Reactive Implemen

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  172 5 Designing a Reactive Implemen

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  174 5 Designing a Reactive Implemen

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  176 5 Designing a Reactive Implemen

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  180 5 Designing a Reactive Implemen

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  182 5 Designing a Reactive Implemen

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  184 5 Designing a Reactive Implemen

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  186 5 Designing a Reactive Implemen

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  188 5 Designing a Reactive Implemen

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  190 5 Designing a Reactive Implemen

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  192 5 Designing a Reactive Implemen

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  6 Common Sensing Techniques for Rea

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  MODALITY LOGICAL SENSORS LOGICAL EQ

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  6.2 Behavioral Sensor Fusion 199 Fi

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  6.2 Behavioral Sensor Fusion 201 se

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  SENSOR SUITE FIELD OF VIEW (FOV) 6.

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  LOCOMOTION LOAD 6.3 Designing a Sen

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  PHYSICAL 6.4 Proprioceptive Sensors

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  6.4 Proprioceptive Sensors 209 tain

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  ECHO SIDE LOBES 6.5 Proximity Senso

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  6.5 Proximity Sensors 213 IV III I

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  6.5 Proximity Sensors 215 a. b. Fig

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  6.5 Proximity Sensors 217 ambient l

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  IMAGE FUNCTION 6.6 Computer Vision

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  6.6 Computer Vision 221 Magenta (25

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  6.6 Computer Vision 223 a. b. Figur

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  6.6 Computer Vision 225 Angle A Ang

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  6.6 Computer Vision 227 Note that t

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  6.6 Computer Vision 229 a. b. c. Fi

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  STEREOPSIS OPTIC FLOW 6.7 Range fro

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  RECTIFIED IMAGES DISPARITY EPIPOLAR

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  6.7 Range from Vision 235 Figure 6.

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  6.7 Range from Vision 237 scene Fin

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  6.7 Range from Vision 239 a. b. Fig

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  LIGHTWEIGHT VISION RADIAL DEPTH MAP

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  6.8 Case Study: Hors d’Oeuvres, A

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  6.8 Case Study: Hors d’Oeuvres, A

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  6.8 Case Study: Hors d’Oeuvres, A

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  6.8 Case Study: Hors d’Oeuvres, A

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  6.10 Exercises 251 most common colo

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  6.10 Exercises 253 Describe the typ

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  6.11 End Notes 255 the morning. As

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  7 The Hybrid Deliberative/Reactive

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  7.2 Attributes of the Hybrid Paradi

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  SKILL VS. BEHAVIOR 7.2 Attributes o

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  7.3 Architectural Aspects 263 mines

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  FAIL UPWARDS AUTONOMOUS ROBOT ARCHI

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  7.4 Managerial Architectures 267 wh

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  7.4 Managerial Architectures 269 re

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  7.4 Managerial Architectures 271 a.

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  7.4 Managerial Architectures 273 In

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  7.5 State-Hierarchy Architectures 2

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  UPDATE RATE. 7.6 Model-Oriented Arc

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  PRS-LITE 7.6 Model-Oriented Archite

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  7.6 Model-Oriented Architectures 28

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  7.7 Other Robots in the Hybrid Para

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  7.9 Interleaving Deliberation and R

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  SELECTIVE ATTENTION 7.9 Interleavin

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  7.11 Exercises 289 rule of thumb is

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  7.12 End Notes 291 Exercise 7.11 [A

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  8 Multi-agents Chapter Objectives:

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  8.1 Overview 295 It is not clear wh

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  8.2 Heterogeneity 297 Each robot wa

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  8.2 Heterogeneity 299 a. Figure 8.2

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  8.3 Control 301 Now consider a case

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  8.4 Cooperation 303 Likewise, there

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  8.6 Emergent Social Behavior 305 no

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  8.6 Emergent Social Behavior 307 Fi

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  8.7 Summary 309 time Robot 1 Robot

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  8.8 Exercises 311 Exercise 8.5 Desc

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  8.9 End Notes 313 computer science.

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  316 Part II TOPOLOGICAL NAVIGATION

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  318 Part II a. b. Figure II.1 Two T

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• Page 341 and 342:

  320 Part II 5. Supports corrections

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  322 Part II 4. Information collecti

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  9 Topological Path Planning Chapter

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  9.2 Landmarks and Gateways 327 perc

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  DISTINCTIVE PLACE 9.3 Relational Me

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  9.3 Relational Methods 331 Metric:

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  ASSOCIATIVE METHODS PERCEPTUAL STAB

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  9.4 Associative Methods 335 Figure

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  9.4 Associative Methods 337 the veh

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  9.5 Case Study of Topological Navig

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  TRANSITION TABLE 9.5 Case Study of

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  9.5 Case Study of Topological Navig

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  9.5 Case Study of Topological Navig

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  9.5 Case Study of Topological Navig

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  9.7 Exercises 349 Exercise 9.7 Desc

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  10 Metric Path Planning Chapter obj

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  CONFIGURATION SPACE DEGREES OF FREE

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  10.3 Cspace Representations 355 Fig

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  10.3 Cspace Representations 357 Fig

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  10.4 Graph Based Planners 359 10.3.

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  10.4 Graph Based Planners 361 The p

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  10.4 Graph Based Planners 363 Figur

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  10.5 Wavefront Based Planners 365 T

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  SUBGOAL OBSESSION OPPORTUNISTIC REP

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  D* ALGORITHM 10.6 Interleaving Path

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  EVENT-DRIVEN 10.7 Summary 371 and m

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  10.8 Exercises 373 Exercise 10.2 Re

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  11 Localization and Map Making Chap

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  11.1 Overview 377 spired much humor

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  11.2 Sonar Sensor Model 379 β III

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  11.3 Bayesian 381 approach presente

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  11.3 Bayesian 383 R=10 β=15 s=6 r=

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  11.3 Bayesian 385 Eqn. 11.4 in boxe

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  11.4 Dempster-Shafer Theory 387 may

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  VACUOUS BELIEF 11.4 Dempster-Shafer

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  11.4 Dempster-Shafer Theory 391 Bel

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  11.4 Dempster-Shafer Theory 393 Bel

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  11.5 HIMM 395 more than two belief

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  (11.11) 11.5 HIMM 397 basic formula

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  11.5 HIMM 399 reading 1 reading 2 0

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  11.5 HIMM 401 cupancy grid. The cen

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  11.6 Comparison of Methods 403 11.6

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  11.6 Comparison of Methods 405 [0][

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  (11.12) (11.13) (11.14) 11.6 Compar

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  (11.15) 11.6 Comparison of Methods

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  11.6 Comparison of Methods 411 m(do

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  3 WAYS TO TUNE 11.6.4 Tuning 11.6 C

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  11.7 Localization 415 often be a di

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  LOCAL OCCUPANCY GLOBAL OCCUPANCY 11

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  11.7 Localization 419 Once the scor

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  11.7 Localization 421 be able to no

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  11.7 Localization 423 3 3-4 4 4-5 5

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  11.8 Exploration 425 readings will

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  11.8 Exploration 427 x_c = x_c/coun

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  11.9 Summary 429 a. b. Figure 11.23

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  11.10 Exercises 431 sor readings. T

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  11.10 Exercises 433 Exercise 11.11

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  12 On the Horizon Chapter Objective

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  12.1 Overview 437 The central theme

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  LEGGED LOCOMOTION 12.2 Shape-Shifti

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  12.2 Shape-Shifting and Legged Plat

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  12.3 Applications and Expectations

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  12.4 Summary 445 limitations, there

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  12.6 End Notes 447 Exercise 12.2 Co

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  Bibliography [1] Albus, J., and Pro

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  Bibliography 451 [28] Brooks, R., C

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  Bibliography 453 [60] Gifford, K.K.

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  Bibliography 455 [92] McKenzie, D.C

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  Bibliography 457 [124] Schöne, H.,

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  Index 3T, 258, 274-277, 283, 284, 2

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  Index 461 differential GPS (DGPS),

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  Index 463 logical equivalence, 197

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  Index 465 schema, 91 schema class,