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A FEW ARE LISTED BELOW:


Artificial Intelligence:
Chapter 1Introduction
1.1 General
1.2 Developments in Artificial Intelligence
1.3 Developments in Expert Systems
1.4 Role of AI and Expert Systems in Engineering
Chapter 2Search Techniques
2.1 Introduction
2.2 Problem Definition and Solution Process
2.3 Production Systems
2.4 Search Techniques
2.4.1 Breadth-First Search
2.4.2 Depth-First Search
2.4.3 Heuristic Search
2.4.4 Generate and Test
2.4.5 Best-First Search
2.4.6 Agenda-Driven Search
2.5 Problem Decomposition and AND-OR Graphs
Chapter 3Knowledge-Based Expert System
3.1 Introduction
3.2 What is KBES?
3.3 Architecture of KBES
3.3.1 Knowledge Base
3.3.2 Inference Mechanisms
3.3.3 Inexact Reasoning
3.3.4 Non-Monotonic Reasoning
3.3.5 Reasoning Based on Certainty Factors
Chapter 4Engineering Design Synthesis
4.1 Introduction
4.2 Synthesis
4.3 Decomposition Model for Synthesis
4.4 Role of a Synthesiser in KBES Environment
4.5 An Architecture for a Synthesiser - A Generic Tool
4.6 Generic Synthesis Tool - GENSYNT
4.6.1 Application Examples
Chapter 5Criticism and Evaluation
5.1 Introduction
5.2 Methodologies Used in a Knowledge-Based Environment
5.3 A Framework for Critiquing and Evaluation
5.3.1 Knowledge Representation Framework
5.3.2 Inference Mechanism
5.3.3 Algorithm for Overall Rating of a Hierarchical Solution
5.4 Generic Critiquing Tool - Gencrit
5.4.1 Critiquing Knowledge Base in GENCRIT
5.4.2 Working of GENCRIT
Chapter 6Case-Based Reasoning
6.1 Introduction
6.2 Applications of Case-Based Reasoning
6.2.1 Planning
6.2.2 Design
6.2.3 Diagnosis
6.3 Case-Based Reasoning Process
6.3.1 Case Retrieval
6.3.1.1 Selection by search conditions
6.3.1.2 Classification by relevance
6.3.1.3 Classification by performance
6.3.1.4 Illustration of the case retrieval process
6.3.2 Solution Transformation
6.3.2.1 Problem detection
6.3.2.2 Focusing on appropriate parts
6.3.2.3 Solution transformation
6.3.2.4 Evaluation and testing
6.3.3 Case Storing
6.4 A Framework for CBR in Engineering Design (CASETOOL)
6.4.1 Case Retrieval
6.4.2 Solution Transformation
6.4.3 Case Storing
6.5 Architecture of CASETOOL
6.6 Application Example
6.6.1 Architecture of VASTU
6.6.2 CBR Process in VASTU
Chapter 7Process Models and Knowledge-Based Systems
7.1 Introduction
7.2 Expert Systems for Diagnosis
7.2.1 Understanding of Domain Knowledge
7.2.2 Evolution of Knowledge Nets
7.2.3 Transformation of Knowledge from Nets to Rule Base
7.3 Blackboard Model of Problem Solving
7.3.1 Blackboard Architecture
7.3.2 Blackboard Framework
7.3.3 Integrated Engineering System
7.3.4 Illustrative Example
7.4 ODESSY - An Integrated System for Preliminary Design of Reinforced Concrete
Multistory Office Buildings
7.4.1 Task Analysis of Building Design
7.4.2 Synthesis-Criticism-Modification Model
7.4.3 Layout Planning
7.4.4 Conceptual and Preliminary Design
7.4.5 Architecture of ODESSY
7.5 Conceptual Design of a Car Body Shape
7.5.1 Functional Requirements
7.5.2 Design Parameters
7.5.3 Design Decoupling
7.5.4 Synthesis and Critiquing of Solutions
7.5.5 Case-Based Evaluation of Shapes
7.6 SETHU - An Integrated KBES for Concrete Road Bridge Design
7.6.1 Task Analysis of Bridge Design Process
7.6.2 Process Model
7.6.3 KBES Development Tool
7.6.4 SETHU: Architecture
7.7 Future Trends
7.7.1 Genetic Algorithms
7.7.2 Artificial Neural Networks
7.7.3 Concurrent Engineering
============================

BUILD A FIGHTING ROBOT:

1 Welcome to Competition Robots 1
2 Getting Started 21
3 Robot Locomotion 41
4 Motor Selection and Performance 61
5 Its All About Power 79
6 Power Transmission: Getting Power to Your Wheels 103
7 Controlling Your Motors 127
8 Remotely Controlling Your Robot 157
9 Robot Material and Construction Techniques 183
10 Weapons Systems for Your Robot 203
11 Autonomous Robots 239
12 Robot Brains 259
13 Robot Sumo 275
14 Real-Life Robots: Lessons from Veteran Builders 305
15 Afterword 329
A Prototyping Electronics 335
B Resources and References 343
C Helpful Formulas 355

==============================

Mobile Robot Design
Robots and Controllers 3
1.1 Mobile Robots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2 Embedded Controllers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.3 Interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.4 Operating System. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
1.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2 Sensors 17
2.1 Sensor Categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.2 Binary Sensor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.3 Analog versus Digital Sensors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.4 Shaft Encoder. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.5 A/D Converter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.6 Position Sensitive Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.7 Compass. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.8 Gyroscope, Accelerometer, Inclinometer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.9 Digital Camera. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.10 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3 Actuators 41
3.1 DC Motors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.2 H-Bridge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.3 Pulse Width Modulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.4 Stepper Motors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.5 Servos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4 Control 51
4.1 On-Off Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
4.2 PID Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
4.3 Velocity Control and Position Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
4.4 Multiple Motors Driving Straight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

================================

Intelligent Autonomous Robotics

. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2. TheClass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
3. InitialBehaviors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
4. Vision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
4.1 Camera Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
4.2 Color Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
4.3 Region Building andMerging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.4 Object Recognition with Bounding Boxes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
4.5 Position and Bearing of Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
4.6 Visual Opponent Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
5. Movement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
5.1 Walking. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27
5.1.1 Basics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27
5.1.2 Forward Kinematics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28
5.1.3 Inverse Kinematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .29
5.1.4 General Walking Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5.1.5 Omnidirectional Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.1.6 Tilting the Body Forward. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35
5.1.7 Tuning the Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
5.1.8 Odometry Calibration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .36
5.2 General Movement. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37
5.2.1 MovementModule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
5.2.2 Movement Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
5.2.3 High-Level Control. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43
5.3 LearningMovement Tasks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44
5.3.1 Forward Gait . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .44
5.3.2 Ball Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
6. FallDetection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .47
viii INTELLIGENT AUTONOMOUS ROBOTICS
7. Kicking. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49
7.1 Creating the Critical Action. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50
7.2 Integrating the Critical Action into theWalk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
8. Localization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
8.1 Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .54
8.1.1 BasicMonte Carlo Localization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55
8.1.2 MCL for Vision-Based Legged Robots . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
8.2 Enhancements to the Basic Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
8.2.1 LandmarkHistories. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57
8.2.2 Distance-Based Updates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59
8.2.3 ExtendedMotionModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
8.3 Experimental Setup and Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
8.3.1 Simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
8.3.2 Experimental Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60
8.3.3 Test for Accuracy and Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
8.3.4 Test for Stability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63
8.3.5 ExtendedMotionModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
8.3.6 Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .65
8.4 Localization Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
9. Communication. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69
9.1 Initial Robot-to-Robot Communication. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69
9.2 Message Types. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70
9.3 KnowingWhich Robots Are Communicating. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70
9.4 DeterminingWhen A Teammate Is Dead . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
9.5 Practical Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71
10. GeneralArchitecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
11. Global Map. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .75
11.1 Maintaining Location Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
11.2 Information from Teammates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
11.3 Providing aHigh-Level Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
12. Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
12.1 Goal Scoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
12.1.1 Initial Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
CONTENTS ix
12.1.2 Incorporating Localization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .80
12.1.3 A Finite StateMachine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
12.2 Goalie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
13. Coordination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
13.1 Dibs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
13.1.1 Relevant Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
13.1.2 Thrashing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87
13.1.3 Stabilization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .88
13.1.4 Taking the Average . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
13.1.5 Aging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
13.1.6 Calling the Ball . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .88
13.1.7 Support Distance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
13.1.8 Phasing out Dibs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
13.2 Final Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .89
13.2.1 Roles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
13.2.2 Supporter Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
13.2.3 Defender Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .91
13.2.4 Dynamic Role Assignment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
14. Simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .95
14.1 Basic Architecture. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .95
14.2 ServerMessages. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .95
14.3 SensorModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .96
14.4 MotionModel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
14.5 Graphical Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .96
15. UTAssist . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
15.1 General Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
15.2 Debugging Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
15.2.1 Visual Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
15.2.2 Localization Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
15.2.3 Miscellaneous Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .102
15.3 Vision Calibration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .102
16. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
A. Heuristics for the Vision Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
A.1 RegionMerging and Pruning Parameters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .107
x INTELLIGENT AUTONOMOUS ROBOTICS
A.2 Tilt-Angle Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .108
A.3 CircleMethod. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
A.4 Beacon Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
A.5 Goal Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
A.6 Ball Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
A.7 Opponent Detection Parameters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .114
A.8 Opponent Blob Likelihood Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
A.9 Coordinate Transforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
A.9.1 Walking Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
B. Kicks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
B.1 Initial Kick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
B.2 Head Kick. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .119
B.3 Chest-Push Kick. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .120
B.4 Arms Together Kick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
B.5 Fall-Forward Kick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
B.6 Back Kick . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
C. TCPGateway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
D. Extension toWorld State in 2004. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .127
E. Simulator Message Grammar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
E.1 Client ActionMessages. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .132
E.2 Client InfoMessages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132
E.3 Simulated SensationMessages. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .132
E.4 Simulated ObservationMessages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
F. CompetitionResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
F.1 American Open 2003. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .135
F.2 RoboCup 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
F.3 Challenge Events 2003 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
F.4 U.S. Open 2004 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
F.5 RoboCup 2004 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
F.6 U.S. Open 2005 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
F.7 RoboCup 2005 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
============================

MODERN ROBOTS

Child Prodigy 2
Brilliant Mathematician 4
Life at MIT 5
Stopping the Bombers 6
I Was There: Wiener Walks 7
Feedback 8
Computers and Controls 8
Neural Networks 10
Toward a New Science 11
Cybernetics 13
Cybernetics and Robotic Turtles 14
The Boston Arm 15
Parallels: Applications of Cybernetics 16
Facing the Social Consequences 17
Chronology 18
Further Reading 20
2 REVOLUTIONIZING INDUSTRY:
JOSEPH ENGELBERGER AND UNIMATE 22
Hands-on Experience 22
Developing Industrial Robots 23
Other Scientists: George Devol (1920 ) 25
Robots on the Assembly Line 25
eCONTENTS
Industrial Robots Today 27
Social Impact: Robots and Human Labor 28
Robots in Service 28
Elder Statesperson of Robotics 31
A Wrong Direction? 31
Trends: The Robotics Industry Today 32
Chronology 33
Further Reading 34
3 LEARNING TO WALK:
MARC RAIBERT AND ROBOTS WITH LEGS 36
Making of an Engineer 37
Dynamic Walkers 38
Robot Kangaroos 40
Boston Dynamics 42
Connections: Beasts and Bots 43
Robot Mules 44
Solving Problems: Robots and Animation 44
A Dynamic Future 46
Chronology 47
Further Reading 48
4 REAL-WORLD ROBOTS:
COLIN ANGLE, HELEN GREINER, AND iROBOT 50
Hands-on Builder 51
Teaming Up: Brooks, Angle, and Greiner 52
Baby Doll 53
Solving Problems: Doing Enough with Less 54
Household Robots: A Different Approach 55
Behavioral Building Blocks 57
Robots on the Front Lines 60
Future Household Robots 60
Honored for Innovation 62
Chronology 62
Further Reading 63
5 ROBOT EXPLORERS:
DONNA SHIRLEY AND THE MARS ROVERS 66
A Love of Engineering 66
Getting Respect 67
Designing Space Robots 68
Connections: Why Arent They Here? 70
Missions to Mars 71
Mariner 9 71
Managing Risk 72
Trends: Milestones in NASAs Mars Exploration 73
Better, Faster, Cheaper 75
Robots and Rovers 76
Sojourners Truth 77
Issues: Should We Send People or Robots
to Explore the Universe? 80
Forging a New Career 81
Chronology 82
Further Reading 83
6 THOUGHTFUL ROBOTS: RODNEY BROOKS AND COG 85
A Passion for Computers 85
Studying Artificial Intelligence 86
The Challenge of Vision 87
A Brainless Robot 88
Parallels: Artificial Life and Artificial Intelligence 90
Robot Insects 92
Humanoid Robots 93
Cog 96
Practical Robotics 97
What Distinguishes Life? 98
Chronology 100
Further Reading 101
7 ROBOT AMBASSADOR: MASATO HIROSE AND ASIMO 103
From Motorcycles to Robotics 103
Learning to Walk 104
Asimo Debuts 106
Other Scientists: Sonys Robot Researchers 108
Robotic Ambassador 110
Future Helpers 111
Other Approaches 111
Issues: Robots and Religion 112
Chronology 113
Further Reading 114
8 SOCIABLE ROBOTS: CYNTHIA BREAZEAL AND KISMET 116
In Love with the Droids 116
From Cog to Kismet 118
Seeing, Hearing, Speaking 119
Issues: What Might It Mean for Robots to Feel? 121
Emotional States 124
Parallels: A Robotic Garden 124
Leonardo 125
The Future of Sociable Robots 126
Social Impact: Women in Robotics 127
A Robot That Can Be Your Friend 128
Chronology 129
Further Reading 130
9 RADICAL ROBOTICIST:
HANS MORAVEC AND THE FUTURE OF ROBOTICS 131
At Home with Robots 132
Robots à la Carte 132
I Was There: Moravec the Hacker 134
Robotic Vehicles 135
Moores Law and the Quest for Robot Intelligence 136
Solving Problems: In the Drivers Seat 137
Issues: Moravec v. Brooks 139
Robots: The Next Generations 140
Meanwhile, Back at the Warehouse 142
Social Impact: Transcendence through Technology? 143
Looking Forward 144
Chronology 145
Further Reading 146
10 CYBORG ODYSSEY:
KEVIN WARWICK EXTENDS THE HUMAN BODY 148
Science, Soccer, and Motorcycles 148
Working World and University 150
Boosting Productivity 151
Helping the Disabled 151
The Seven Dwarfs 152
Solving Problems: Safer Baths 153
Hello, Mr. Chip 154
I Was There: Robot Bumper Cars 155
From Humans to Cyborgs 155
Issues: Convenience v. Privacy 156
Cyborg 2.0: The Neural Implant Project 158
Cyborg Experiments 159
The Human Connection 160
An Open Future 160
Social Impact: Enhanced vs. Normal 162
Chronology 164
Further Reading 165

===============================

PDA ROBOTS

1 Anatomy of a Personal Digital Assistant (PDA) 1
2 Robotic System Overview 15
3 Tools and Equipment 23
4 Infrared Communications Overview 29
5 The Electronics 43
6 Building PDA Robot 107
7 Programming the PIC16F876 Microcontroller 137
8 PDA Robot Palm OS Software Using
Code Warrior 8.0 155

===============================

Practical Artificial Intelligence JAVA

Table of Contents
Practical Artificial Intelligence Programming in Java.................................................................. 1
byMark Watson. Copyright 2001-2002. All rights reserved................................................... 1
Preface..................................................................................................................................... 5
Acknowledgements ............................................................................................................... 5
Introduction .............................................................................................................................. 6
Notes for users of UNIX and Linux....................................................................................... 7
Use of the Unified Modeling Language (UML) in this book................................................... 8
Chapter 1. Search.................................................................................................................... 12
1.1 Representation of State Space, Nodes in Search Trees and Search Operators................. 12
1.2 Finding paths in mazes................................................................................................... 14
1.3 Finding Paths in Graphs ................................................................................................. 24
1.4 Adding heuristics to Breadth First Search ...................................................................... 33
1.5 Search and Game Playing .............................................................................................. 33
1.5.1 Alpha-Beta search ...................................................................................................... 34
1.5.2 A Java Framework for Search and Game Playing ........................................................ 36
1.5.3 TicTacToe using the alpha beta search algorithm........................................................ 42
1.5.4 Chess using the alpha beta search algorithm................................................................ 48
https://www.tradebit.comhod name.............................................................................................................. 58
Percent of total runtime ....................................................................................................... 58
Percent in this method only.................................................................................................. 58
Chapter 2. Natural Language Processing ................................................................................. 60
2.1 ATN Parsers.................................................................................................................. 61
2.1.1 Lexicon data for defining word types .......................................................................... 65
2.1.2 Design and implementation of an ATN parser in Java.................................................. 66
2.1.3 Testing the Java ATN parser....................................................................................... 73
2.2 Natural Language Interfaces for Databases .................................................................... 75
2.2.2 History of the NLBean development ........................................................................... 76
2.2.3 Design of the NLP Database Interface ........................................................................ 77
2.2.4 Implementation of the NLP Database Interface ........................................................... 79
2.2.4.1 DBInfo class............................................................................................................ 79
Copyright 2001 byMark Watson page 3 of 3 1/20/2002 08:48:15
2.2.4.2 DBInterface class..................................................................................................... 81
2.2.4.3 Help class ................................................................................................................ 81
2.2.4.4 MakeTestDB class................................................................................................... 82
2.2.4.5 NLBean class........................................................................................................... 82
2.2.4.6 NLEngine class........................................................................................................ 83
2.2.4.7 NLP class ................................................................................................................ 83
2.2.4.8 SmartDate class ....................................................................................................... 85
2.2.5 Running the NLBean NLP System.............................................................................. 85
2.3 Using Prolog for NLP.................................................................................................... 86
2.3.1 Prolog examples of parsing simple English sentences .................................................. 86
2.3.2 Embedding Prolog rules in a Java application.............................................................. 90
Chapter 3. Expert Systems ...................................................................................................... 94
3.1 A tutorial on writing expert systems with Jess................................................................ 95
3.2 Implementing a reasoning system with Jess .................................................................. 102
Chapter 4. Genetic Algorithms .............................................................................................. 110
4.1 Java classes for Genetic Algorithms ............................................................................. 116
4.2 Example System for solving polynomial regression problems ....................................... 120
Chapter 5. Neural networks................................................................................................... 125
5.1 Hopfield neural networks............................................................................................. 126
5.2 Java classes for Hopfield neural networks .................................................................... 128
5.3 Testing the Hopfield neural network example class ...................................................... 131
5.5 Backpropagation neural networks................................................................................ 133
5.6 A Java class library and examples for using back propagation neural networks ............. 137
5.7 Notes on using back propagation neural networks ....................................................... 147
6. Machine Learning using Weka........................................................................................... 149
6.1 Using machine learning to induce a set of production rules........................................... 149
6.2 A sample learning problem........................................................................................... 150
6.3 Running Weka............................................................................................................. 152
Index.................................................................................................................................... 154
Bibliography......................................................................................................................... 156
===============================

DESIGN YOUR OWN ROBOT:
Introduction Making a Robot
1 Robot Behaviour
2 Robot Mechanics
3 Robot Electronics
4 PICs in Control
5 PIC Programming
6 Projects
The Scooter
The Android
A robotic toy
The Quester
The gantry
Index
=========================

Scientific Methods in
Mobile Robotics

A Brief Introduction to Mobile Robotics . . . . . . . . . . . . . . . . . . . . . 1
1.1 This Book is not about Mobile Robotics . . . . . . . . . . . . . . . . . . . . . 1
1.2 What is Mobile Robotics? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.3 The Emergence of Behaviour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4 Examples of Research Issues in Autonomous Mobile Robotics . . 7
1.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2 Introduction to Scientific Methods in Mobile Robotics . . . . . . . . . . 11
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2 Motivation: Analytical Robotics . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3 Robot-Environment Interaction as Computation . . . . . . . . . . . . . . 15
2.4 A Theory of Robot-Environment Interaction . . . . . . . . . . . . . . . . . 16
2.5 Robot Engineering vs Robot Science . . . . . . . . . . . . . . . . . . . . . . . . 18
2.6 Scientific Method and Autonomous Mobile Robotics . . . . . . . . . . 19
2.7 Tools Used in this Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.8 Summary: The Contrast Between
Experimental Mobile Robotics and Scientific Mobile Robotics . . 28
3 Statistical Tools for Describing Experimental Data . . . . . . . . . . . . . 29
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.2 The Normal Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.3 Parametric Methods to Compare Samples . . . . . . . . . . . . . . . . . . . . 33
3.4 Non-Parametric Methods to Compare Samples . . . . . . . . . . . . . . . 43
3.5 Testing for Randomness in a Sequence . . . . . . . . . . . . . . . . . . . . . . 55
3.6 Parametric Tests for a Trend (Correlation Analysis) . . . . . . . . . . . 57
3.7 Non-Parametric Tests for a Trend . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.8 Analysing Categorical Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.9 Principal Component Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
xiii
xiv Contents
4 Dynamical Systems Theory and Agent Behaviour . . . . . . . . . . . . . . 85
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
4.2 Dynamical Systems Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
4.3 Describing (Robot) Behaviour Quantitatively Through Phase
Space Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
4.4 Sensitivity to Initial Conditions: The Lyapunov Exponent . . . . . . 100
4.5 Aperiodicity: The Dimension of Attractors . . . . . . . . . . . . . . . . . . . 116
4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
5 Analysis of Agent BehaviourCase Studies . . . . . . . . . . . . . . . . . 121
5.1 Analysing the Movement of a Random-Walk Mobile Robot . . . . . 121
5.2 Chaos Walker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
5.3 Analysing the Flight Paths of Carrier Pigeons . . . . . . . . . . . . . . . . 133
6 Computer Modelling of Robot-Environment Interaction . . . . . . . . 139
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
6.2 Some Practical Considerations Regarding Robot Modelling . . . . . 141
6.3 Case Study: Model Acquisition Using Artificial Neural Networks 143
6.4 Linear Polynomial Models and Linear Recurrence Relations . . . . 150
6.5 NARMAX Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
6.6 Accurate Simulation: Environment Identification . . . . . . . . . . . . . . 156
6.7 Task Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
6.8 Sensor Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
6.9 When Are Two Behaviours the Same? . . . . . . . . . . . . . . . . . . . . . . 185
6.10 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193
7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
7.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
7.2 Quantitative Descriptions of Robot-Environment Interaction . . . . 196
7.3 A Theory of Robot-Environment Interaction . . . . . . . . . . . . . . . . . 197
7.4 Outlook: Towards Analytical Robotics . . . . . . . . . . . . . . . . . . . . . . 199
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
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