{"title":"Robotics Books","description":"","products":[{"product_id":"talking-to-robots-9781472142917","title":"Talking to Robots","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003e''A refreshing variation on the will-intelligent-robots-bring-Armageddon genre . . . this colorful mixture of expert futurology and quirky speculation does not disappoint''\u003cbr\u003e \u003ci\u003eKirkus\u003c\/i\u003e\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e''A robot may not injure a human being or, through inaction, allow a human being to come to harm.'' Isaac Asimov, \u003ci\u003eThe First Law of Robotics\u003c\/i\u003e\u003cbr\u003e\u003cbr\u003eWhat robot and AI systems are being built and imagined right now? What do they say about us, their creators? Will they usher in a fantastic new future, or destroy us? 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Frame 52\u003c\/p\u003e \u003cp\u003e2.6.5 Mixed Transformations Relative to Rotating and Reference Frames 53\u003c\/p\u003e \u003cp\u003e2.7 Inverse of Transformation Matrices 54\u003c\/p\u003e \u003cp\u003e2.8 Forward and Inverse Kinematics of Robots 59\u003c\/p\u003e \u003cp\u003e2.9 Forward and Inverse Kinematic Equations: Position 60\u003c\/p\u003e \u003cp\u003e2.9.1 Cartesian (Gantry, Rectangular) Coordinates 60\u003c\/p\u003e \u003cp\u003e2.9.2 Cylindrical Coordinates 61\u003c\/p\u003e \u003cp\u003e2.9.3 Spherical Coordinates 63\u003c\/p\u003e \u003cp\u003e2.9.4 Articulated Coordinates 65\u003c\/p\u003e \u003cp\u003e2.10 Forward and Inverse Kinematic Equations: Orientation 65\u003c\/p\u003e \u003cp\u003e2.10.1 Roll, Pitch, Yaw (RPY) Angles 65\u003c\/p\u003e \u003cp\u003e2.10.2 Euler Angles 68\u003c\/p\u003e \u003cp\u003e2.10.3 Articulated Joints 70\u003c\/p\u003e \u003cp\u003e2.11 Forward and Inverse Kinematic Equations: Position and Orientation 70\u003c\/p\u003e \u003cp\u003e2.12 Denavit-Hartenberg Representation of Forward Kinematic Equations of Robots 70\u003c\/p\u003e \u003cp\u003e2.13 The Inverse Kinematic Solution of Robots 84\u003c\/p\u003e \u003cp\u003e2.13.1 General Solution for Articulated Robot Arms 86\u003c\/p\u003e \u003cp\u003e2.14 Inverse Kinematic Programming of Robots 89\u003c\/p\u003e \u003cp\u003e2.15 Dual-Arm Cooperating Robots 91\u003c\/p\u003e \u003cp\u003e2.16 Degeneracy and Dexterity 92\u003c\/p\u003e \u003cp\u003e2.16.1 Degeneracy 92\u003c\/p\u003e \u003cp\u003e2.16.2 Dexterity 93\u003c\/p\u003e \u003cp\u003e2.17 The Fundamental Problem with the Denavit-Hartenberg Representation 93\u003c\/p\u003e \u003cp\u003e2.18 Design Projects 95\u003c\/p\u003e \u003cp\u003e2.18.1 Stair-Climbing Robot 96\u003c\/p\u003e \u003cp\u003e2.18.2 A 3-DOF Robot 96\u003c\/p\u003e \u003cp\u003e2.18.3 A 3-DOF Mobile Robot 98\u003c\/p\u003e \u003cp\u003e2.19 Summary 99\u003c\/p\u003e \u003cp\u003eReferences 99\u003c\/p\u003e \u003cp\u003eProblems 99\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Robot Kinematics with Screw-Based Mechanics 111\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 111\u003c\/p\u003e \u003cp\u003e3.2 What Is a Screw? 111\u003c\/p\u003e \u003cp\u003e3.3 Rotation about a Screw Axis 112\u003c\/p\u003e \u003cp\u003e3.4 Homogenous Transformations about a General Screw Axis 115\u003c\/p\u003e \u003cp\u003e3.5 Successive Screw-Based Transformations 119\u003c\/p\u003e \u003cp\u003e3.6 Forward and Inverse Position Analysis of an Articulated Robot 120\u003c\/p\u003e \u003cp\u003e3.7 Design Projects 127\u003c\/p\u003e \u003cp\u003e3.8 Summary 127\u003c\/p\u003e \u003cp\u003eAdditional Reading 128\u003c\/p\u003e \u003cp\u003eProblems 128\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Kinematics Analysis of Parallel Robots 133\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 133\u003c\/p\u003e \u003cp\u003e4.2 Physical Characteristics of Parallel Robots 134\u003c\/p\u003e \u003cp\u003e4.3 The Denavit-Hartenberg Approach vs. the Direct Kinematic Approach 139\u003c\/p\u003e \u003cp\u003e4.4 Forward and Inverse Kinematics of Planar Parallel Robots 140\u003c\/p\u003e \u003cp\u003e4.4.1 Kinematic Analysis of a 3-RPR Planar Parallel Robot 141\u003c\/p\u003e \u003cp\u003e4.4.2 Kinematic Analysis of a 3-RRR Planar Parallel Robot 143\u003c\/p\u003e \u003cp\u003e4.5 Forward and Inverse Kinematics of Spatial Parallel Robots 147\u003c\/p\u003e \u003cp\u003e4.5.1 Kinematic Analysis of a Generic 6-6 Stewart-Gough Platform 147\u003c\/p\u003e \u003cp\u003e4.5.2 Kinematic Analysis of a Generic 6-3 Stewart-Gough Platform 152\u003c\/p\u003e \u003cp\u003e4.5.3 Kinematic Analysis of a 3-Axis RSS-Type Parallel Robot 154\u003c\/p\u003e \u003cp\u003e4.5.4 Kinematic Analysis of a 4-Axis RSS-Type Parallel Robot 160\u003c\/p\u003e \u003cp\u003e4.5.5 Kinematic Analysis of a 3-Axis PSS-Type Parallel Robot 167\u003c\/p\u003e \u003cp\u003e4.6 Other Parallel Robot Configurations 169\u003c\/p\u003e \u003cp\u003e4.7 Design Projects 169\u003c\/p\u003e \u003cp\u003e4.8 Summary 170\u003c\/p\u003e \u003cp\u003eReferences 170\u003c\/p\u003e \u003cp\u003eProblems 170\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Differential Motions and Velocities 173\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 173\u003c\/p\u003e \u003cp\u003e5.2 Differential Relationships 173\u003c\/p\u003e \u003cp\u003e5.3 The Jacobian 174\u003c\/p\u003e \u003cp\u003e5.4 Differential versus Large-Scale Motions 176\u003c\/p\u003e \u003cp\u003e5.5 Differential Motions of a Frame versus a Robot 177\u003c\/p\u003e \u003cp\u003e5.6 Differential Motions of a Frame 178\u003c\/p\u003e \u003cp\u003e5.6.1 Differential Translations 178\u003c\/p\u003e \u003cp\u003e5.6.2 Differential Rotations about Reference Axes 178\u003c\/p\u003e \u003cp\u003e5.6.3 Differential Rotation about a General Axis q 179\u003c\/p\u003e \u003cp\u003e5.6.4 Differential Transformations of a Frame 181\u003c\/p\u003e \u003cp\u003e5.7 Interpretation of the Differential Change 182\u003c\/p\u003e \u003cp\u003e5.8 Differential Changes between Frames 183\u003c\/p\u003e \u003cp\u003e5.9 Differential Motions of a Robot and Its Hand Frame 185\u003c\/p\u003e \u003cp\u003e5.10 Calculation of the Jacobian 185\u003c\/p\u003e \u003cp\u003e5.11 How to Relate the Jacobian and the Differential Operator 188\u003c\/p\u003e \u003cp\u003e5.12 The Inverse Jacobian 191\u003c\/p\u003e \u003cp\u003e5.13 Calculation of the Jacobian with Screw-Based Mechanics 197\u003c\/p\u003e \u003cp\u003e5.14 The Inverse Jacobian for the Screw-Based Method 206\u003c\/p\u003e \u003cp\u003e5.15 Calculation of the Jacobians of Parallel Robots 206\u003c\/p\u003e \u003cp\u003e5.15.1 The Jacobian of a Planar 3-RRR Parallel Robot 207\u003c\/p\u003e \u003cp\u003e5.15.2 The Jacobian of a Generic 6-6 Stewart-Gough Parallel Robot 208\u003c\/p\u003e \u003cp\u003e5.16 Design Projects 210\u003c\/p\u003e \u003cp\u003e5.16.1 The 3-DOF Robot 210\u003c\/p\u003e \u003cp\u003e5.16.2 The 3-DOF Mobile Robot 210\u003c\/p\u003e \u003cp\u003e5.17 Summary 210\u003c\/p\u003e \u003cp\u003eReferences 211\u003c\/p\u003e \u003cp\u003eProblems 211\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Dynamic and Force Analysis 219\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 219\u003c\/p\u003e \u003cp\u003e6.2 Lagrangian Mechanics: A Short Overview 220\u003c\/p\u003e \u003cp\u003e6.3 Effective Moments of Inertia 229\u003c\/p\u003e \u003cp\u003e6.4 Dynamic Equations for Multiple-DOF Robots 229\u003c\/p\u003e \u003cp\u003e6.4.1 Kinetic Energy 229\u003c\/p\u003e \u003cp\u003e6.4.2 Potential Energy 234\u003c\/p\u003e \u003cp\u003e6.4.3 The Lagrangian 234\u003c\/p\u003e \u003cp\u003e6.4.4 Robot’s Equations of Motion 234\u003c\/p\u003e \u003cp\u003e6.5 Static Force Analysis of Robots 239\u003c\/p\u003e \u003cp\u003e6.6 Transformation of Forces and Moments between Coordinate Frames 242\u003c\/p\u003e \u003cp\u003e6.7 Design Project 244\u003c\/p\u003e \u003cp\u003e6.8 Summary 244\u003c\/p\u003e \u003cp\u003eReferences 244\u003c\/p\u003e \u003cp\u003eProblems 245\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Trajectory Planning 247\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 247\u003c\/p\u003e \u003cp\u003e7.2 Path vs. Trajectory 247\u003c\/p\u003e \u003cp\u003e7.3 Joint-Space vs. Cartesian-Space Descriptions 248\u003c\/p\u003e \u003cp\u003e7.4 Basics of Trajectory Planning 249\u003c\/p\u003e \u003cp\u003e7.5 Joint-Space Trajectory Planning 252\u003c\/p\u003e \u003cp\u003e7.5.1 Third-Order Polynomial Trajectory Planning 252\u003c\/p\u003e \u003cp\u003e7.5.2 Fifth-Order Polynomial Trajectory Planning 255\u003c\/p\u003e \u003cp\u003e7.5.3 Linear Segments with Parabolic Blends 257\u003c\/p\u003e \u003cp\u003e7.5.4 Linear Segments with Parabolic Blends and Via Points 259\u003c\/p\u003e \u003cp\u003e7.5.5 Higher-Order Trajectories 260\u003c\/p\u003e \u003cp\u003e7.5.6 Other Trajectories 263\u003c\/p\u003e \u003cp\u003e7.6 Cartesian-Space Trajectories 263\u003c\/p\u003e \u003cp\u003e7.7 Continuous Trajectory Recording 267\u003c\/p\u003e \u003cp\u003e7.8 Design Project 268\u003c\/p\u003e \u003cp\u003e7.9 Summary 269\u003c\/p\u003e \u003cp\u003eReferences 269\u003c\/p\u003e \u003cp\u003eProblems 269\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Motion Control Systems 273\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 273\u003c\/p\u003e \u003cp\u003e8.2 Basic Components and Terminology 273\u003c\/p\u003e \u003cp\u003e8.3 Block Diagrams 274\u003c\/p\u003e \u003cp\u003e8.4 System Dynamics 274\u003c\/p\u003e \u003cp\u003e8.5 Laplace Transform 278\u003c\/p\u003e \u003cp\u003e8.6 Inverse Laplace Transform 281\u003c\/p\u003e \u003cp\u003e8.6.1 Partial Fraction Expansion When F(s) Involves Only Distinct Poles 281\u003c\/p\u003e \u003cp\u003e8.6.2 Partial Fraction Expansion When F(s) Involves Repeated Poles 282\u003c\/p\u003e \u003cp\u003e8.6.3 Partial Fraction Expansion When F(s) Involves Complex Conjugate Poles 283\u003c\/p\u003e \u003cp\u003e8.7 Transfer Functions 285\u003c\/p\u003e \u003cp\u003e8.8 Block Diagram Algebra 288\u003c\/p\u003e \u003cp\u003e8.9 Characteristics of First-Order Transfer Functions 290\u003c\/p\u003e \u003cp\u003e8.10 Characteristics of Second-Order Transfer Functions 292\u003c\/p\u003e \u003cp\u003e8.11 Characteristic Equation: Pole\/Zero Mapping 294\u003c\/p\u003e \u003cp\u003e8.12 Steady-State Error 296\u003c\/p\u003e \u003cp\u003e8.13 Root Locus Method 298\u003c\/p\u003e \u003cp\u003e8.14 Proportional Controllers 303\u003c\/p\u003e \u003cp\u003e8.15 Proportional-Plus-Integral Controllers 306\u003c\/p\u003e \u003cp\u003e8.16 Proportional-Plus-Derivative Controllers 308\u003c\/p\u003e \u003cp\u003e8.17 Proportional-Integral-Derivative Controller (PID) 311\u003c\/p\u003e \u003cp\u003e8.18 Lead and Lag Compensators 313\u003c\/p\u003e \u003cp\u003e8.19 Bode Diagram and Frequency-Domain Analysis 313\u003c\/p\u003e \u003cp\u003e8.20 Open-Loop vs. Closed-Loop Applications 314\u003c\/p\u003e \u003cp\u003e8.21 Multiple-Input and Multiple-Output Systems 314\u003c\/p\u003e \u003cp\u003e8.22 State-Space Control Methodology 316\u003c\/p\u003e \u003cp\u003e8.23 Digital Control 320\u003c\/p\u003e \u003cp\u003e8.24 Nonlinear Control Systems 322\u003c\/p\u003e \u003cp\u003e8.25 Electromechanical Systems Dynamics: Robot Actuation and Control 323\u003c\/p\u003e \u003cp\u003e8.26 Design Projects 326\u003c\/p\u003e \u003cp\u003e8.27 Summary 327\u003c\/p\u003e \u003cp\u003eReferences 327\u003c\/p\u003e \u003cp\u003eProblems 327\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Actuators and Drive Systems 331\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 331\u003c\/p\u003e \u003cp\u003e9.2 Characteristics of Actuating Systems 331\u003c\/p\u003e \u003cp\u003e9.2.1 Nominal Characteristics – Weight, Power-to-Weight Ratio, Operating Pressure, Voltage, and Others 331\u003c\/p\u003e \u003cp\u003e9.2.2 Stiffness vs. Compliance 332\u003c\/p\u003e \u003cp\u003e9.2.3 Use of Reduction Gears 332\u003c\/p\u003e \u003cp\u003e9.3 Comparison of Actuating Systems 335\u003c\/p\u003e \u003cp\u003e9.4 Hydraulic Actuators 335\u003c\/p\u003e \u003cp\u003e9.5 Pneumatic Devices 337\u003c\/p\u003e \u003cp\u003e9.6 Electric Motors 338\u003c\/p\u003e \u003cp\u003e9.6.1 Fundamental Differences Between AC- and DC-Type Motors 339\u003c\/p\u003e \u003cp\u003e9.6.2 DC Motors 341\u003c\/p\u003e \u003cp\u003e9.6.3 AC Motors 344\u003c\/p\u003e \u003cp\u003e9.6.4 Brushless DC Motors 345\u003c\/p\u003e \u003cp\u003e9.6.5 Direct-Drive Electric Motors 346\u003c\/p\u003e \u003cp\u003e9.6.6 Servomotors 346\u003c\/p\u003e \u003cp\u003e9.6.7 Stepper Motors 347\u003c\/p\u003e \u003cp\u003e9.7 Microprocessor Control of Electric Motors 360\u003c\/p\u003e \u003cp\u003e9.7.1 Pulse Width Modulation 361\u003c\/p\u003e \u003cp\u003e9.7.2 Direction Control of DC Motors with an H-Bridge 363\u003c\/p\u003e \u003cp\u003e9.8 Magnetostrictive Actuators 364\u003c\/p\u003e \u003cp\u003e9.9 Shape-Memory Type Metals 364\u003c\/p\u003e \u003cp\u003e9.10 Electroactive Polymer Actuators (EAPs) 364\u003c\/p\u003e \u003cp\u003e9.11 Speed Reduction 365\u003c\/p\u003e \u003cp\u003e9.12 Other Systems 367\u003c\/p\u003e \u003cp\u003e9.13 Design Projects 367\u003c\/p\u003e \u003cp\u003e9.14 Summary 370\u003c\/p\u003e \u003cp\u003eReferences 371\u003c\/p\u003e \u003cp\u003eProblems 372\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Sensors 375\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 375\u003c\/p\u003e \u003cp\u003e10.2 Sensor Characteristics 375\u003c\/p\u003e \u003cp\u003e10.3 Sensor Utilization 377\u003c\/p\u003e \u003cp\u003e10.4 Position Sensors 378\u003c\/p\u003e \u003cp\u003e10.4.1 Potentiometers 378\u003c\/p\u003e \u003cp\u003e10.4.2 Encoders 379\u003c\/p\u003e \u003cp\u003e10.4.3 Linear Variable Differential Transformer (LVDT) 382\u003c\/p\u003e \u003cp\u003e10.4.4 Resolvers 383\u003c\/p\u003e \u003cp\u003e10.4.5 (Linear) Magnetostrictive Displacement Transducer (LMDT or MDT) 383\u003c\/p\u003e \u003cp\u003e10.4.6 Hall-effect Sensors 384\u003c\/p\u003e \u003cp\u003e10.4.7 Global Positioning System (GPS) 384\u003c\/p\u003e \u003cp\u003e10.4.8 Other Devices 385\u003c\/p\u003e \u003cp\u003e10.5 Velocity Sensors 385\u003c\/p\u003e \u003cp\u003e10.5.1 Encoders 385\u003c\/p\u003e \u003cp\u003e10.5.2 Tachometers 385\u003c\/p\u003e \u003cp\u003e10.5.3 Differentiation of Position Signal 386\u003c\/p\u003e \u003cp\u003e10.6 Acceleration Sensors 386\u003c\/p\u003e \u003cp\u003e10.7 Force and Pressure Sensors 386\u003c\/p\u003e \u003cp\u003e10.7.1 Piezoelectric 386\u003c\/p\u003e \u003cp\u003e10.7.2 Force-Sensing Resistor 386\u003c\/p\u003e \u003cp\u003e10.7.3 Strain Gauge 387\u003c\/p\u003e \u003cp\u003e10.7.4 Antistatic Foam 388\u003c\/p\u003e \u003cp\u003e10.8 Torque Sensors 388\u003c\/p\u003e \u003cp\u003e10.9 Microswitches 389\u003c\/p\u003e \u003cp\u003e10.10 Visible Light and Infrared Sensors 389\u003c\/p\u003e \u003cp\u003e10.11 Touch and Tactile Sensors 390\u003c\/p\u003e \u003cp\u003e10.12 Proximity Sensors 391\u003c\/p\u003e \u003cp\u003e10.12.1 Magnetic Proximity Sensors 391\u003c\/p\u003e \u003cp\u003e10.12.2 Optical Proximity Sensors 391\u003c\/p\u003e \u003cp\u003e10.12.3 Ultrasonic Proximity Sensors 392\u003c\/p\u003e \u003cp\u003e10.12.4 Inductive Proximity Sensors 392\u003c\/p\u003e \u003cp\u003e10.12.5 Capacitive Proximity Sensors 393\u003c\/p\u003e \u003cp\u003e10.12.6 Eddy Current Proximity Sensors 393\u003c\/p\u003e \u003cp\u003e10.13 Range Finders 393\u003c\/p\u003e \u003cp\u003e10.13.1 Ultrasonic Range Finders 394\u003c\/p\u003e \u003cp\u003e10.13.2 Light-Based Range Finders 395\u003c\/p\u003e \u003cp\u003e10.14 Sniff Sensors 396\u003c\/p\u003e \u003cp\u003e10.15 Vision Systems 396\u003c\/p\u003e \u003cp\u003e10.16 Voice-Recognition Devices 396\u003c\/p\u003e \u003cp\u003e10.17 Voice Synthesizers 397\u003c\/p\u003e \u003cp\u003e10.18 Remote Center Compliance (RCC) Device 397\u003c\/p\u003e \u003cp\u003e10.19 Design Project 400\u003c\/p\u003e \u003cp\u003e10.20 Summary 400\u003c\/p\u003e \u003cp\u003eReferences 401\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Image Processing and Analysis with Vision Systems 403\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 403\u003c\/p\u003e \u003cp\u003e11.2 Basic Concepts 403\u003c\/p\u003e \u003cp\u003e11.2.1 Image Processing vs. Image Analysis 403\u003c\/p\u003e \u003cp\u003e11.2.2 Two- and Three-Dimensional Image Types 403\u003c\/p\u003e \u003cp\u003e11.2.3 The Nature of an Image 404\u003c\/p\u003e \u003cp\u003e11.2.4 Acquisition of Images 405\u003c\/p\u003e \u003cp\u003e11.2.5 Digital Images 405\u003c\/p\u003e \u003cp\u003e11.2.6 Frequency Domain vs. Spatial Domain 406\u003c\/p\u003e \u003cp\u003e11.3 Fourier Transform and Frequency Content of a Signal 406\u003c\/p\u003e \u003cp\u003e11.4 Frequency Content of an Image: Noise and Edges 409\u003c\/p\u003e \u003cp\u003e11.5 Resolution and Quantization 410\u003c\/p\u003e \u003cp\u003e11.6 Sampling Theorem 412\u003c\/p\u003e \u003cp\u003e11.7 Image-Processing Techniques 415\u003c\/p\u003e \u003cp\u003e11.8 Histograms of Images 415\u003c\/p\u003e \u003cp\u003e11.9 Thresholding 418\u003c\/p\u003e \u003cp\u003e11.10 Spatial Domain Operations Convolution Mask 419\u003c\/p\u003e \u003cp\u003e11.11 Connectivity 424\u003c\/p\u003e \u003cp\u003e11.12 Noise Reduction 426\u003c\/p\u003e \u003cp\u003e11.12.1 Neighborhood Averaging with Convolution Masks 427\u003c\/p\u003e \u003cp\u003e11.12.2 Image Averaging 428\u003c\/p\u003e \u003cp\u003e11.12.3 Frequency Domain 429\u003c\/p\u003e \u003cp\u003e11.12.4 Median Filters 429\u003c\/p\u003e \u003cp\u003e11.13 Edge Detection 430\u003c\/p\u003e \u003cp\u003e11.14 Sharpening an Image 436\u003c\/p\u003e \u003cp\u003e11.15 Hough Transform 437\u003c\/p\u003e \u003cp\u003e11.16 Segmentation 440\u003c\/p\u003e \u003cp\u003e11.17 Segmentation by Region Growing and Region Splitting 441\u003c\/p\u003e \u003cp\u003e11.18 Binary Morphology Operations 444\u003c\/p\u003e \u003cp\u003e11.18.1 Thickening Operation 446\u003c\/p\u003e \u003cp\u003e11.18.2 Dilation 446\u003c\/p\u003e \u003cp\u003e11.18.3 Erosion 447\u003c\/p\u003e \u003cp\u003e11.18.4 Skeletonization 447\u003c\/p\u003e \u003cp\u003e11.18.5 Open Operation 448\u003c\/p\u003e \u003cp\u003e11.18.6 Close Operation 448\u003c\/p\u003e \u003cp\u003e11.18.7 Fill Operation 448\u003c\/p\u003e \u003cp\u003e11.19 Gray Morphology Operations 449\u003c\/p\u003e \u003cp\u003e11.19.1 Erosion 449\u003c\/p\u003e \u003cp\u003e11.19.2 Dilation 449\u003c\/p\u003e \u003cp\u003e11.20 Image Analysis 449\u003c\/p\u003e \u003cp\u003e11.21 Object Recognition by Features 450\u003c\/p\u003e \u003cp\u003e11.21.1 Basic Features Used for Object Identification 450\u003c\/p\u003e \u003cp\u003e11.21.2 Moments 451\u003c\/p\u003e \u003cp\u003e11.21.3 Template Matching 456\u003c\/p\u003e \u003cp\u003e11.21.4 Discrete Fourier Descriptors 456\u003c\/p\u003e \u003cp\u003e11.21.5 Computed Tomography (CT) 457\u003c\/p\u003e \u003cp\u003e11.22 Depth Measurement with Vision Systems 457\u003c\/p\u003e \u003cp\u003e11.22.1 Scene Analysis vs. Mapping 457\u003c\/p\u003e \u003cp\u003e11.22.2 Range Detection and Depth Analysis 458\u003c\/p\u003e \u003cp\u003e11.22.3 Stereo Imaging 458\u003c\/p\u003e \u003cp\u003e11.22.4 Scene Analysis with Shading and Sizes 459\u003c\/p\u003e \u003cp\u003e11.23 Specialized Lighting 459\u003c\/p\u003e \u003cp\u003e11.24 Image Data Compression 460\u003c\/p\u003e \u003cp\u003e11.24.1 Intraframe Spatial Domain Techniques 460\u003c\/p\u003e \u003cp\u003e11.24.2 Interframe Coding 461\u003c\/p\u003e \u003cp\u003e11.24.3 Compression Techniques 461\u003c\/p\u003e \u003cp\u003e11.25 Color Images 462\u003c\/p\u003e \u003cp\u003e11.26 Heuristics 462\u003c\/p\u003e \u003cp\u003e11.27 Applications of Vision Systems 462\u003c\/p\u003e \u003cp\u003e11.28 Design Project 463\u003c\/p\u003e \u003cp\u003e11.29 Summary 464\u003c\/p\u003e \u003cp\u003eReferences 464\u003c\/p\u003e \u003cp\u003eProblems 465\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Fuzzy Logic Control 475\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 475\u003c\/p\u003e \u003cp\u003e12.2 Fuzzy Control: What Is Needed 476\u003c\/p\u003e \u003cp\u003e12.3 Crisp Values vs. Fuzzy Values 476\u003c\/p\u003e \u003cp\u003e12.4 Fuzzy Sets: Degrees of Truth and Membership 477\u003c\/p\u003e \u003cp\u003e12.5 Fuzzification 477\u003c\/p\u003e \u003cp\u003e12.6 Fuzzy Inference Rules 480\u003c\/p\u003e \u003cp\u003e12.7 Defuzzification 481\u003c\/p\u003e \u003cp\u003e12.7.1 Center of Gravity Method 481\u003c\/p\u003e \u003cp\u003e12.7.2 Mamdani Inference Method 481\u003c\/p\u003e \u003cp\u003e12.8 Simulation of a Fuzzy Logic Controller 485\u003c\/p\u003e \u003cp\u003e12.9 Applications of Fuzzy Logic in Robotics 487\u003c\/p\u003e \u003cp\u003e12.10 Design Project 488\u003c\/p\u003e \u003cp\u003e12.11 Summary 489\u003c\/p\u003e \u003cp\u003eReferences 489\u003c\/p\u003e \u003cp\u003eProblems 490\u003c\/p\u003e \u003cp\u003eAppendix A 491\u003c\/p\u003e \u003cp\u003eAppendix B 499\u003c\/p\u003e \u003cp\u003eIndex 501\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":48738361475415,"sku":"9781119527626","price":107.96,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119527626.jpg?v=1723811974"},{"product_id":"cyberphysicalhuman-systems-9781119857402","title":"CyberPhysicalHuman Systems","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eCyberPhysicalHuman Systems\u003c\/b\u003e \u003cp\u003e\u003cb\u003eA comprehensive edited volume exploring the latest in the interactions between cyberphysical systems and humans\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eIn \u003ci\u003eCyberPhysicalHuman Systems: Fundamentals and Applications\u003c\/i\u003e, a team of distinguished researchers delivers a robust and up-to-date volume of contributions from leading researchers on CyberPhysicalHuman Systems, an emerging class of systems with increased interactions between cyberphysical, and human systems communicating with each other at various levels across space and time, so as to achieve desired performance related to human welfare, efficiency, and sustainability. \u003c\/p\u003e\u003cp\u003eThe editors have focused on papers that address the power of emerging CPHS disciplines, all of which feature humans as an active component during cyber and physical interactions. Articles that span fundamental concepts and methods to various applications in engineering sectors of transportation, robotics, and healthcare and general socio-technical system\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eA Note from the Series Editor xvii\u003c\/p\u003e \u003cp\u003eAbout the Editors xviii\u003c\/p\u003e \u003cp\u003eList of Contributors xix\u003c\/p\u003e \u003cp\u003eIntroduction xxvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I Fundamental Concepts and Methods 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Human-in-the-Loop Control and Cyber–Physical–Human Systems: Applications and Categorization 3\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eTariq Samad\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 3\u003c\/p\u003e \u003cp\u003e1.2 Cyber + Physical + Human 4\u003c\/p\u003e \u003cp\u003e1.2.1 Cyberphysical Systems 5\u003c\/p\u003e \u003cp\u003e1.2.2 Physical–Human Systems 6\u003c\/p\u003e \u003cp\u003e1.2.3 Cyber–Human Systems 6\u003c\/p\u003e \u003cp\u003e1.3 Categorizing Human-in-the-Loop Control Systems 6\u003c\/p\u003e \u003cp\u003e1.3.1 Human-in-the-Plant 8\u003c\/p\u003e \u003cp\u003e1.3.2 Human-in-the-Controller 8\u003c\/p\u003e \u003cp\u003e1.3.3 Human–Machine Control Symbiosis 10\u003c\/p\u003e \u003cp\u003e1.3.4 Humans-in-Multiagent-Loops 11\u003c\/p\u003e \u003cp\u003e1.4 A Roadmap for Human-in-the-Loop Control 13\u003c\/p\u003e \u003cp\u003e1.4.1 Self- and Human-Driven Cars on Urban Roads 13\u003c\/p\u003e \u003cp\u003e1.4.2 Climate Change Mitigation and Smart Grids 14\u003c\/p\u003e \u003cp\u003e1.5 Discussion 15\u003c\/p\u003e \u003cp\u003e1.5.1 Other Ways of Classifying Human-in-the-Loop Control 15\u003c\/p\u003e \u003cp\u003e1.5.2 Modeling Human Understanding and Decision-Making 16\u003c\/p\u003e \u003cp\u003e1.5.3 Ethics and CPHS 18\u003c\/p\u003e \u003cp\u003e1.6 Conclusions 19\u003c\/p\u003e \u003cp\u003eAcknowledgments 19\u003c\/p\u003e \u003cp\u003eReferences 20\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Human Behavioral Models Using Utility Theory and Prospect Theory 25\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAnuradha M. Annaswamy and Vineet Jagadeesan Nair\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 25\u003c\/p\u003e \u003cp\u003e2.2 Utility Theory 26\u003c\/p\u003e \u003cp\u003e2.2.1 An Example 27\u003c\/p\u003e \u003cp\u003e2.3 Prospect Theory 27\u003c\/p\u003e \u003cp\u003e2.3.1 An Example: CPT Modeling for SRS 30\u003c\/p\u003e \u003cp\u003e2.3.1.1 Detection of CPT Effects via Lotteries 32\u003c\/p\u003e \u003cp\u003e2.3.2 Theoretical Implications of CPT 33\u003c\/p\u003e \u003cp\u003e2.3.2.1 Implication I: Fourfold Pattern of Risk Attitudes 34\u003c\/p\u003e \u003cp\u003e2.3.2.2 Implication II: Strong Risk Aversion Over Mixed Prospects 36\u003c\/p\u003e \u003cp\u003e2.3.2.3 Implication III: Effects of Self-Reference 37\u003c\/p\u003e \u003cp\u003e2.4 Summary and Conclusions 38\u003c\/p\u003e \u003cp\u003eAcknowledgments 39\u003c\/p\u003e \u003cp\u003eReferences 39\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Social Diffusion Dynamics in Cyber–Physical–Human Systems 43\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eLorenzo Zino and Ming Cao\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 43\u003c\/p\u003e \u003cp\u003e3.2 General Formalism for Social Diffusion in CPHS 45\u003c\/p\u003e \u003cp\u003e3.2.1 Complex and Multiplex Networks 45\u003c\/p\u003e \u003cp\u003e3.2.2 General Framework for Social Diffusion 46\u003c\/p\u003e \u003cp\u003e3.2.3 Main Theoretical Approaches 48\u003c\/p\u003e \u003cp\u003e3.3 Modeling Decision-Making 49\u003c\/p\u003e \u003cp\u003e3.3.1 Pairwise Interaction Models 49\u003c\/p\u003e \u003cp\u003e3.3.2 Linear Threshold Models 52\u003c\/p\u003e \u003cp\u003e3.3.3 Game-Theoretic Models 53\u003c\/p\u003e \u003cp\u003e3.4 Dynamics in CPHS 55\u003c\/p\u003e \u003cp\u003e3.4.1 Social Diffusion in Multiplex Networks 56\u003c\/p\u003e \u003cp\u003e3.4.2 Co-Evolutionary Social Dynamics 58\u003c\/p\u003e \u003cp\u003e3.5 Ongoing Efforts Toward Controlling Social Diffusion and Future Challenges 62\u003c\/p\u003e \u003cp\u003eAcknowledgments 63\u003c\/p\u003e \u003cp\u003eReferences 63\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Opportunities and Threats of Interactions Between Humans and Cyber–Physical Systems – Integration and Inclusion Approaches for Cphs 71\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eFrédéric Vanderhaegen and Victor Díaz Benito Jiménez\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 CPHS and Shared Control 72\u003c\/p\u003e \u003cp\u003e4.2 “Tailor-made” Principles for Human–CPS Integration 73\u003c\/p\u003e \u003cp\u003e4.3 “All-in-one” based Principles for Human–CPS Inclusion 74\u003c\/p\u003e \u003cp\u003e4.4 Dissonances, Opportunities, and Threats in a CPHS 76\u003c\/p\u003e \u003cp\u003e4.5 Examples of Opportunities and Threats 79\u003c\/p\u003e \u003cp\u003e4.6 Conclusions 85\u003c\/p\u003e \u003cp\u003eReferences 86\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Enabling Human-Aware Autonomy Through Cognitive Modeling and Feedback Control 91\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eNeera Jain, Tahira Reid, Kumar Akash, Madeleine Yuh, and Jacob Hunter\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 91\u003c\/p\u003e \u003cp\u003e5.1.1 Important Cognitive Factors in HAI 92\u003c\/p\u003e \u003cp\u003e5.1.2 Challenges with Existing CPHS Methods 93\u003c\/p\u003e \u003cp\u003e5.1.3 How to Read This Chapter 95\u003c\/p\u003e \u003cp\u003e5.2 Cognitive Modeling 95\u003c\/p\u003e \u003cp\u003e5.2.1 Modeling Considerations 95\u003c\/p\u003e \u003cp\u003e5.2.2 Cognitive Architectures 97\u003c\/p\u003e \u003cp\u003e5.2.3 Computational Cognitive Models 98\u003c\/p\u003e \u003cp\u003e5.2.3.1 ARMAV and Deterministic Linear Models 99\u003c\/p\u003e \u003cp\u003e5.2.3.2 Dynamic Bayesian Models 99\u003c\/p\u003e \u003cp\u003e5.2.3.3 Decision Analytical Models 100\u003c\/p\u003e \u003cp\u003e5.2.3.4 POMDP Models 102\u003c\/p\u003e \u003cp\u003e5.3 Study Design and Data Collection 103\u003c\/p\u003e \u003cp\u003e5.3.1 Frame Research Questions and Identify Variables 104\u003c\/p\u003e \u003cp\u003e5.3.2 Formulate Hypotheses or Determine the Data Needed 105\u003c\/p\u003e \u003cp\u003e5.3.2.1 Hypothesis Testing Approach 105\u003c\/p\u003e \u003cp\u003e5.3.2.2 Model Training Approach 105\u003c\/p\u003e \u003cp\u003e5.3.3 Design Experiment and\/or Study Scenario 107\u003c\/p\u003e \u003cp\u003e5.3.3.1 Hypothesis Testing Approach 107\u003c\/p\u003e \u003cp\u003e5.3.3.2 Model Training Approach 107\u003c\/p\u003e \u003cp\u003e5.3.4 Conduct Pilot Studies and Get Initial Feedback; Do Preliminary Analysis 108\u003c\/p\u003e \u003cp\u003e5.3.5 A Note about Institutional Review Boards and Recruiting Participants 109\u003c\/p\u003e \u003cp\u003e5.4 Cognitive Feedback Control 109\u003c\/p\u003e \u003cp\u003e5.4.1 Considerations for Feedback Control 110\u003c\/p\u003e \u003cp\u003e5.4.2 Approaches 111\u003c\/p\u003e \u003cp\u003e5.4.2.1 Heuristics-Based Planning 111\u003c\/p\u003e \u003cp\u003e5.4.2.2 Measurement-Based Feedback 112\u003c\/p\u003e \u003cp\u003e5.4.2.3 Goal-Oriented Feedback 112\u003c\/p\u003e \u003cp\u003e5.4.2.4 Case Study 112\u003c\/p\u003e \u003cp\u003e5.4.3 Evaluation Methods 113\u003c\/p\u003e \u003cp\u003e5.5 Summary and Opportunities for Further Investigation 113\u003c\/p\u003e \u003cp\u003e5.5.1 Model Generalizability and Adaptability 114\u003c\/p\u003e \u003cp\u003e5.5.2 Measurement of Cognitive States 114\u003c\/p\u003e \u003cp\u003e5.5.3 Human Subject Study Design 114\u003c\/p\u003e \u003cp\u003eReferences 115\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Shared Control with Human Trust and Workload Models 125\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMurat Cubuktepe, Nils Jansen, and Ufuk Topcu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 125\u003c\/p\u003e \u003cp\u003e6.1.1 Review of Shared Control Methods 126\u003c\/p\u003e \u003cp\u003e6.1.2 Contribution and Approach 127\u003c\/p\u003e \u003cp\u003e6.1.3 Review of IRL Methods Under Partial Information 128\u003c\/p\u003e \u003cp\u003e6.1.3.1 Organization 129\u003c\/p\u003e \u003cp\u003e6.2 Preliminaries 129\u003c\/p\u003e \u003cp\u003e6.2.1 Markov Decision Processes 129\u003c\/p\u003e \u003cp\u003e6.2.2 Partially Observable Markov Decision Processes 130\u003c\/p\u003e \u003cp\u003e6.2.3 Specifications 130\u003c\/p\u003e \u003cp\u003e6.3 Conceptual Description of Shared Control 131\u003c\/p\u003e \u003cp\u003e6.4 Synthesis of the Autonomy Protocol 132\u003c\/p\u003e \u003cp\u003e6.4.1 Strategy Blending 132\u003c\/p\u003e \u003cp\u003e6.4.2 Solution to the Shared Control Synthesis Problem 133\u003c\/p\u003e \u003cp\u003e6.4.2.1 Nonlinear Programming Formulation for POMDPs 133\u003c\/p\u003e \u003cp\u003e6.4.2.2 Strategy Repair Using Sequential Convex Programming 134\u003c\/p\u003e \u003cp\u003e6.4.3 Sequential Convex Programming Formulation 135\u003c\/p\u003e \u003cp\u003e6.4.4 Linearizing Nonconvex Problem 135\u003c\/p\u003e \u003cp\u003e6.4.4.1 Linearizing Nonconvex Constraints and Adding Slack Variables 135\u003c\/p\u003e \u003cp\u003e6.4.4.2 Trust Region Constraints 136\u003c\/p\u003e \u003cp\u003e6.4.4.3 Complete Algorithm 136\u003c\/p\u003e \u003cp\u003e6.4.4.4 Additional Specifications 136\u003c\/p\u003e \u003cp\u003e6.4.4.5 Additional Measures 137\u003c\/p\u003e \u003cp\u003e6.5 Numerical Examples 137\u003c\/p\u003e \u003cp\u003e6.5.1 Modeling Robot Dynamics as POMDPs 138\u003c\/p\u003e \u003cp\u003e6.5.2 Generating Human Demonstrations 138\u003c\/p\u003e \u003cp\u003e6.5.3 Learning a Human Strategy 139\u003c\/p\u003e \u003cp\u003e6.5.4 Task Specification 139\u003c\/p\u003e \u003cp\u003e6.5.5 Results 140\u003c\/p\u003e \u003cp\u003e6.6 Conclusion 140\u003c\/p\u003e \u003cp\u003eAcknowledgments 140\u003c\/p\u003e \u003cp\u003eReferences 140\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Parallel Intelligence for CPHS: An ACP Approach 145\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eXiao Wang, Jing Yang, Xiaoshuang Li, and Fei-Yue Wang\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Background and Motivation 145\u003c\/p\u003e \u003cp\u003e7.2 Early Development in China 147\u003c\/p\u003e \u003cp\u003e7.3 Key Elements and Framework 149\u003c\/p\u003e \u003cp\u003e7.4 Operation and Process 151\u003c\/p\u003e \u003cp\u003e7.4.1 Construction of Artificial Systems 152\u003c\/p\u003e \u003cp\u003e7.4.2 Computational Experiments in Parallel Intelligent Systems 152\u003c\/p\u003e \u003cp\u003e7.4.3 Closed-Loop Optimization Based on Parallel Execution 153\u003c\/p\u003e \u003cp\u003e7.5 Applications 153\u003c\/p\u003e \u003cp\u003e7.5.1 Parallel Control and Intelligent Control 154\u003c\/p\u003e \u003cp\u003e7.5.2 Parallel Robotics and Parallel Manufacturing 156\u003c\/p\u003e \u003cp\u003e7.5.3 Parallel Management and Intelligent Organizations 157\u003c\/p\u003e \u003cp\u003e7.5.4 Parallel Medicine and Smart Healthcare 158\u003c\/p\u003e \u003cp\u003e7.5.5 Parallel Ecology and Parallel Societies 160\u003c\/p\u003e \u003cp\u003e7.5.6 Parallel Economic Systems and Social Computing 161\u003c\/p\u003e \u003cp\u003e7.5.7 Parallel Military Systems 163\u003c\/p\u003e \u003cp\u003e7.5.8 Parallel Cognition and Parallel Philosophy 164\u003c\/p\u003e \u003cp\u003e7.6 Conclusion and Prospect 165\u003c\/p\u003e \u003cp\u003eReferences 165\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Transportation 171\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Regularities of Human Operator Behavior and Its Modeling 173\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAleksandr V. Efremov\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 173\u003c\/p\u003e \u003cp\u003e8.2 The Key Variables in Man–Machine Systems 174\u003c\/p\u003e \u003cp\u003e8.3 Human Responses 177\u003c\/p\u003e \u003cp\u003e8.4 Regularities of Man–Machine System in Manual Control 180\u003c\/p\u003e \u003cp\u003e8.4.1 Man–Machine System in Single-loop Compensatory System 180\u003c\/p\u003e \u003cp\u003e8.4.2 Man–Machine System in Multiloop, Multichannel, and Multimodal Tasks 185\u003c\/p\u003e \u003cp\u003e8.4.2.1 Man–Machine System in the Multiloop Tracking Task 185\u003c\/p\u003e \u003cp\u003e8.4.2.2 Man–Machine System in the Multichannel Tracking Task 187\u003c\/p\u003e \u003cp\u003e8.4.2.3 Man–Machine System in Multimodal Tracking Tasks 188\u003c\/p\u003e \u003cp\u003e8.4.2.4 Human Operator Behavior in Pursuit and Preview Tracking Tasks 191\u003c\/p\u003e \u003cp\u003e8.5 Mathematical Modeling of Human Operator Behavior in Manual Control Task 194\u003c\/p\u003e \u003cp\u003e8.5.1 McRuer’s Model for the Pilot Describing Function 194\u003c\/p\u003e \u003cp\u003e8.5.1.1 Single-Loop Compensatory Model 194\u003c\/p\u003e \u003cp\u003e8.5.1.2 Multiloop and Multimodal Compensatory Model 197\u003c\/p\u003e \u003cp\u003e8.5.2 Structural Human Operator Model 197\u003c\/p\u003e \u003cp\u003e8.5.3 Pilot Optimal Control Model 199\u003c\/p\u003e \u003cp\u003e8.5.4 Pilot Models in Preview and Pursuit Tracking Tasks 201\u003c\/p\u003e \u003cp\u003e8.6 Applications of the Man–Machine System Approach 202\u003c\/p\u003e \u003cp\u003e8.6.1 Development of Criteria for Flying Qualities and PIO Prediction 203\u003c\/p\u003e \u003cp\u003e8.6.1.1 Criteria of FQ and PIO Prediction as a Requirement for the Parameters of the Pilot-Aircraft System 203\u003c\/p\u003e \u003cp\u003e8.6.1.2 Calculated Piloting Rating of FQ as the Criteria 205\u003c\/p\u003e \u003cp\u003e8.6.2 Interfaces Design 206\u003c\/p\u003e \u003cp\u003e8.6.3 Optimization of Control System and Vehicle Dynamics Parameters 210\u003c\/p\u003e \u003cp\u003e8.7 Future Research Challenges and Visions 213\u003c\/p\u003e \u003cp\u003e8.8 Conclusion 214\u003c\/p\u003e \u003cp\u003eReferences 215\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Safe Shared Control Between Pilots and Autopilots in the Face of Anomalies 219\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eEmre Eraslan, Yildiray Yildiz, and Anuradha M. Annaswamy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 219\u003c\/p\u003e \u003cp\u003e9.2 Shared Control Architectures: A Taxonomy 221\u003c\/p\u003e \u003cp\u003e9.3 Recent Research Results 222\u003c\/p\u003e \u003cp\u003e9.3.1 Autopilot 224\u003c\/p\u003e \u003cp\u003e9.3.1.1 Dynamic Model of the Aircraft 224\u003c\/p\u003e \u003cp\u003e9.3.1.2 Advanced Autopilot Based on Adaptive Control 225\u003c\/p\u003e \u003cp\u003e9.3.1.3 Autopilot Based on Proportional Derivative Control 228\u003c\/p\u003e \u003cp\u003e9.3.2 Human Pilot 228\u003c\/p\u003e \u003cp\u003e9.3.2.1 Pilot Models in the Absence of Anomaly 228\u003c\/p\u003e \u003cp\u003e9.3.2.2 Pilot Models in the Presence of Anomaly 229\u003c\/p\u003e \u003cp\u003e9.3.3 Shared Control 230\u003c\/p\u003e \u003cp\u003e9.3.3.1 SCA1: A Pilot with a CfM-Based Perception and a Fixed-Gain Autopilot 231\u003c\/p\u003e \u003cp\u003e9.3.3.2 SCA2: A Pilot with a CfM-Based Decision-Making and an Advanced Adaptive Autopilot 232\u003c\/p\u003e \u003cp\u003e9.3.4 Validation with Human-in-the-Loop Simulations 232\u003c\/p\u003e \u003cp\u003e9.3.5 Validation of Shared Control Architecture 1 234\u003c\/p\u003e \u003cp\u003e9.3.5.1 Experimental Setup 234\u003c\/p\u003e \u003cp\u003e9.3.5.2 Anomaly 235\u003c\/p\u003e \u003cp\u003e9.3.5.3 Experimental Procedure 235\u003c\/p\u003e \u003cp\u003e9.3.5.4 Details of the Human Subjects 236\u003c\/p\u003e \u003cp\u003e9.3.5.5 Pilot-Model Parameters 237\u003c\/p\u003e \u003cp\u003e9.3.5.6 Results and Observations 237\u003c\/p\u003e \u003cp\u003e9.3.6 Validation of Shared Control Architecture 2 240\u003c\/p\u003e \u003cp\u003e9.3.6.1 Experimental Setup 241\u003c\/p\u003e \u003cp\u003e9.3.6.2 Anomaly 241\u003c\/p\u003e \u003cp\u003e9.3.6.3 Experimental Procedure 242\u003c\/p\u003e \u003cp\u003e9.3.6.4 Details of the Human Subjects 243\u003c\/p\u003e \u003cp\u003e9.3.6.5 Results and Observations 244\u003c\/p\u003e \u003cp\u003e9.4 Summary and Future Work 246\u003c\/p\u003e \u003cp\u003eReferences 247\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Safe Teleoperation of Connected and Automated Vehicles 251\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eFrank J. Jiang, Jonas Mårtensson, and Karl H. Johansson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 251\u003c\/p\u003e \u003cp\u003e10.2 Safe Teleoperation 254\u003c\/p\u003e \u003cp\u003e10.2.1 The Advent of 5G 258\u003c\/p\u003e \u003cp\u003e10.3 CPHS Design Challenges in Safe Teleoperation 259\u003c\/p\u003e \u003cp\u003e10.4 Recent Research Advances 261\u003c\/p\u003e \u003cp\u003e10.4.1 Enhancing Operator Perception 261\u003c\/p\u003e \u003cp\u003e10.4.2 Safe Shared Autonomy 264\u003c\/p\u003e \u003cp\u003e10.5 Future Research Challenges 267\u003c\/p\u003e \u003cp\u003e10.5.1 Full Utilization of V2X Networks 267\u003c\/p\u003e \u003cp\u003e10.5.2 Mixed Autonomy Traffic Modeling 268\u003c\/p\u003e \u003cp\u003e10.5.3 5G Experimentation 268\u003c\/p\u003e \u003cp\u003e10.6 Conclusions 269\u003c\/p\u003e \u003cp\u003eReferences 270\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Charging Behavior of Electric Vehicles 273\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eQing-Shan Jia and Teng Long\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 History, Challenges, and Opportunities 274\u003c\/p\u003e \u003cp\u003e11.1.1 The History and Status Quo of EVs 274\u003c\/p\u003e \u003cp\u003e11.1.2 The Current Challenge 276\u003c\/p\u003e \u003cp\u003e11.1.3 The Opportunities 277\u003c\/p\u003e \u003cp\u003e11.2 Data Sets and Problem Modeling 278\u003c\/p\u003e \u003cp\u003e11.2.1 Data Sets of EV Charging Behavior 278\u003c\/p\u003e \u003cp\u003e11.2.1.1 Trend Data Sets 279\u003c\/p\u003e \u003cp\u003e11.2.1.2 Driving Data Sets 279\u003c\/p\u003e \u003cp\u003e11.2.1.3 Battery Data Sets 279\u003c\/p\u003e \u003cp\u003e11.2.1.4 Charging Data Sets 279\u003c\/p\u003e \u003cp\u003e11.2.2 Problem Modeling 281\u003c\/p\u003e \u003cp\u003e11.3 Control and Optimization Methods 284\u003c\/p\u003e \u003cp\u003e11.3.1 The Difficulty of the Control and Optimization 284\u003c\/p\u003e \u003cp\u003e11.3.2 Charging Location Selection and Routing Optimization 285\u003c\/p\u003e \u003cp\u003e11.3.3 Charging Process Control 286\u003c\/p\u003e \u003cp\u003e11.3.4 Control and Optimization Framework 287\u003c\/p\u003e \u003cp\u003e11.3.4.1 Centralized Optimization 287\u003c\/p\u003e \u003cp\u003e11.3.4.2 Decentralized Optimization 288\u003c\/p\u003e \u003cp\u003e11.3.4.3 Hierarchical Optimization 288\u003c\/p\u003e \u003cp\u003e11.3.5 The Impact of Human Behaviors 289\u003c\/p\u003e \u003cp\u003e11.4 Conclusion and Discussion 289\u003c\/p\u003e \u003cp\u003eReferences 290\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III Robotics 299\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Trust-Triggered Robot–Human Handovers Using Kinematic Redundancy for Collaborative Assembly in Flexible Manufacturing 301\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eS. M. Mizanoor Rahman, Behzad Sadrfaridpour, Ian D. Walker, and Yue Wang\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 301\u003c\/p\u003e \u003cp\u003e12.2 The Task Context and the Handover 303\u003c\/p\u003e \u003cp\u003e12.3 The Underlying Trust Model 304\u003c\/p\u003e \u003cp\u003e12.4 Trust-Based Handover Motion Planning Algorithm 305\u003c\/p\u003e \u003cp\u003e12.4.1 The Overall Motion Planning Strategy 305\u003c\/p\u003e \u003cp\u003e12.4.2 Manipulator Kinematics and Kinetics Models 305\u003c\/p\u003e \u003cp\u003e12.4.3 Dynamic Impact Ellipsoid 306\u003c\/p\u003e \u003cp\u003e12.4.4 The Novel Motion Control Approach 307\u003c\/p\u003e \u003cp\u003e12.4.5 Illustration of the Novel Algorithm 308\u003c\/p\u003e \u003cp\u003e12.5 Development of the Experimental Settings 310\u003c\/p\u003e \u003cp\u003e12.5.1 Experimental Setup 310\u003c\/p\u003e \u003cp\u003e12.5.1.1 Type I: Center Console Assembly 310\u003c\/p\u003e \u003cp\u003e12.5.1.2 Type II: Hose Assembly 311\u003c\/p\u003e \u003cp\u003e12.5.2 Real-Time Measurement and Display of Trust 311\u003c\/p\u003e \u003cp\u003e12.5.2.1 Type I: Center Console Assembly 311\u003c\/p\u003e \u003cp\u003e12.5.2.2 Type II: Hose Assembly 313\u003c\/p\u003e \u003cp\u003e12.5.2.3 Trust Computation 313\u003c\/p\u003e \u003cp\u003e12.5.3 Plans to Execute the Trust-Triggered Handover Strategy 314\u003c\/p\u003e \u003cp\u003e12.5.3.1 Type I Assembly 314\u003c\/p\u003e \u003cp\u003e12.5.3.2 Type II Assembly 314\u003c\/p\u003e \u003cp\u003e12.6 Evaluation of the Motion Planning Algorithm 315\u003c\/p\u003e \u003cp\u003e12.6.1 Objective 315\u003c\/p\u003e \u003cp\u003e12.6.2 Experiment Design 315\u003c\/p\u003e \u003cp\u003e12.6.3 Evaluation Scheme 315\u003c\/p\u003e \u003cp\u003e12.6.4 Subjects 316\u003c\/p\u003e \u003cp\u003e12.6.5 Experimental Procedures 316\u003c\/p\u003e \u003cp\u003e12.6.5.1 Type I Assembly 317\u003c\/p\u003e \u003cp\u003e12.6.5.2 Type II Assembly 317\u003c\/p\u003e \u003cp\u003e12.7 Results and Analyses, Type I Assembly 318\u003c\/p\u003e \u003cp\u003e12.8 Results and Analyses, Type II Assembly 322\u003c\/p\u003e \u003cp\u003e12.9 Conclusions and Future Work 323\u003c\/p\u003e \u003cp\u003eAcknowledgment 324\u003c\/p\u003e \u003cp\u003eReferences 324\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Fusing Electrical Stimulation and Wearable Robots with Humans to Restore and Enhance Mobility 329\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eThomas Schauer, Eduard Fosch-Villaronga, and Juan C. Moreno\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 329\u003c\/p\u003e \u003cp\u003e13.1.1 Functional Electrical Stimulation 330\u003c\/p\u003e \u003cp\u003e13.1.2 Spinal Cord Stimulation 331\u003c\/p\u003e \u003cp\u003e13.1.3 Wearable Robotics (WR) 332\u003c\/p\u003e \u003cp\u003e13.1.4 Fusing FES\/SCS and Wearable Robotics 334\u003c\/p\u003e \u003cp\u003e13.2 Control Challenges 335\u003c\/p\u003e \u003cp\u003e13.2.1 Feedback Approaches to Promote Volition 336\u003c\/p\u003e \u003cp\u003e13.2.2 Principles of Assist-as-Needed 336\u003c\/p\u003e \u003cp\u003e13.2.3 Tracking Control Problem Formulation 336\u003c\/p\u003e \u003cp\u003e13.2.4 Co-operative Control Strategies 337\u003c\/p\u003e \u003cp\u003e13.2.5 EMG- and MMG-Based Assessment of Muscle Activation 344\u003c\/p\u003e \u003cp\u003e13.3 Examples 345\u003c\/p\u003e \u003cp\u003e13.3.1 A Hybrid Robotic System for Arm Training of Stroke Survivors 345\u003c\/p\u003e \u003cp\u003e13.3.2 First Certified Hybrid Robotic Exoskeleton for Gait Rehabilitation Settings 347\u003c\/p\u003e \u003cp\u003e13.3.3 Body Weight-Supported Robotic Gait Training with tSCS 348\u003c\/p\u003e \u003cp\u003e13.3.4 Modular FES and Wearable Robots to Customize Hybrid Solutions 348\u003c\/p\u003e \u003cp\u003e13.4 Transfer into Daily Practice: Integrating Ethical, Legal, and Societal Aspects into the Design 350\u003c\/p\u003e \u003cp\u003e13.5 Summary and Outlook 352\u003c\/p\u003e \u003cp\u003eAcknowledgments 353\u003c\/p\u003e \u003cp\u003eAcronyms 353\u003c\/p\u003e \u003cp\u003eReferences 354\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Contemporary Issues and Advances in Human–Robot Collaborations 365\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eTakeshi Hatanaka, Junya Yamauchi, Masayuki Fujita, and Hiroyuki Handa\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Overview of Human–Robot Collaborations 365\u003c\/p\u003e \u003cp\u003e14.1.1 Task Architecture 366\u003c\/p\u003e \u003cp\u003e14.1.2 Human–Robot Team Formation 368\u003c\/p\u003e \u003cp\u003e14.1.3 Human Modeling: Control and Decision 369\u003c\/p\u003e \u003cp\u003e14.1.4 Human Modeling: Other Human Factors 371\u003c\/p\u003e \u003cp\u003e14.1.5 Industrial Perspective 372\u003c\/p\u003e \u003cp\u003e14.1.6 What Is in This Chapter 375\u003c\/p\u003e \u003cp\u003e14.2 Passivity-Based Human-Enabled Multirobot Navigation 376\u003c\/p\u003e \u003cp\u003e14.2.1 Architecture Design 377\u003c\/p\u003e \u003cp\u003e14.2.2 Human Passivity Analysis 379\u003c\/p\u003e \u003cp\u003e14.2.3 Human Workload Analysis 381\u003c\/p\u003e \u003cp\u003e14.3 Operation Support with Variable Autonomy via Gaussian Process 383\u003c\/p\u003e \u003cp\u003e14.3.1 Design of the Operation Support System with Variable Autonomy 385\u003c\/p\u003e \u003cp\u003e14.3.2 User Study 388\u003c\/p\u003e \u003cp\u003e14.3.2.1 Operational Verification 388\u003c\/p\u003e \u003cp\u003e14.3.2.2 Usability Test 390\u003c\/p\u003e \u003cp\u003e14.4 Summary 391\u003c\/p\u003e \u003cp\u003eAcknowledgments 393\u003c\/p\u003e \u003cp\u003eReferences 393\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV Healthcare 401\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Overview and Perspectives on the Assessment and Mitigation of Cognitive Fatigue in Operational Settings 403\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMike Salomone, Michel Audiffren, and Bruno Berberian\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 403\u003c\/p\u003e \u003cp\u003e15.2 Cognitive Fatigue 404\u003c\/p\u003e \u003cp\u003e15.2.1 Definition 404\u003c\/p\u003e \u003cp\u003e15.2.2 Origin of Cognitive Fatigue 404\u003c\/p\u003e \u003cp\u003e15.2.3 Effects on Adaptive Capacities 406\u003c\/p\u003e \u003cp\u003e15.3 Cyber–Physical System and Cognitive Fatigue: More Automation Does Not Imply Less Cognitive Fatigue 406\u003c\/p\u003e \u003cp\u003e15.4 Assessing Cognitive Fatigue 409\u003c\/p\u003e \u003cp\u003e15.4.1 Subjective Measures 409\u003c\/p\u003e \u003cp\u003e15.4.2 Behavioral Measures 410\u003c\/p\u003e \u003cp\u003e15.4.3 Physiological Measurements 410\u003c\/p\u003e \u003cp\u003e15.5 Limitations and Benefits of These Measures 412\u003c\/p\u003e \u003cp\u003e15.6 Current and Future Solutions and Countermeasures 412\u003c\/p\u003e \u003cp\u003e15.6.1 Physiological Computing: Toward Real-Time Detection and Adaptation 412\u003c\/p\u003e \u003cp\u003e15.7 System Design and Explainability 414\u003c\/p\u003e \u003cp\u003e15.8 Future Challenges 415\u003c\/p\u003e \u003cp\u003e15.8.1 Generalizing the Results Observed in the Laboratory to Ecological Situations 415\u003c\/p\u003e \u003cp\u003e15.8.2 Determining the Specificity of Cognitive Fatigue 415\u003c\/p\u003e \u003cp\u003e15.8.3 Recovering from Cognitive Fatigue 417\u003c\/p\u003e \u003cp\u003e15.9 Conclusion 418\u003c\/p\u003e \u003cp\u003eReferences 419\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Epidemics Spread Over Networks: Influence of Infrastructure and Opinions 429\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eBaike She, Sebin Gracy, Shreyas Sundaram, Henrik Sandberg, Karl H. Johansson, andPhilipE.Paré\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 429\u003c\/p\u003e \u003cp\u003e16.1.1 Infectious Diseases 429\u003c\/p\u003e \u003cp\u003e16.1.2 Modeling Epidemic Spreading Processes 430\u003c\/p\u003e \u003cp\u003e16.1.3 Susceptible–Infected–Susceptible (SIS) Compartmental Models 431\u003c\/p\u003e \u003cp\u003e16.2 Epidemics on Networks 432\u003c\/p\u003e \u003cp\u003e16.2.1 Motivation 432\u003c\/p\u003e \u003cp\u003e16.2.2 Modeling Epidemics over Networks 433\u003c\/p\u003e \u003cp\u003e16.2.3 Networked Susceptible–Infected–Susceptible Epidemic Models 434\u003c\/p\u003e \u003cp\u003e16.3 Epidemics and Cyber–Physical–Human Systems 436\u003c\/p\u003e \u003cp\u003e16.3.1 Epidemic and Opinion Spreading Processes 437\u003c\/p\u003e \u003cp\u003e16.3.2 Epidemic and Infrastructure 438\u003c\/p\u003e \u003cp\u003e16.4 Recent Research Advances 439\u003c\/p\u003e \u003cp\u003e16.4.1 Notation 439\u003c\/p\u003e \u003cp\u003e16.4.2 Epidemic and Opinion Spreading Processes 440\u003c\/p\u003e \u003cp\u003e16.4.2.1 Opinions Over Networks with Both Cooperative and Antagonistic Interactions 440\u003c\/p\u003e \u003cp\u003e16.4.2.2 Coupled Epidemic and Opinion Dynamics 441\u003c\/p\u003e \u003cp\u003e16.4.2.3 Opinion-Dependent Reproduction Number 443\u003c\/p\u003e \u003cp\u003e16.4.2.4 Simulations 444\u003c\/p\u003e \u003cp\u003e16.4.3 Epidemic Spreading with Shared Resources 445\u003c\/p\u003e \u003cp\u003e16.4.3.1 The Multi-Virus SIWS Model 445\u003c\/p\u003e \u003cp\u003e16.4.3.2 Problem Statements 447\u003c\/p\u003e \u003cp\u003e16.4.3.3 Analysis of the Eradicated State of a Virus 448\u003c\/p\u003e \u003cp\u003e16.4.3.4 Persistence of a Virus 449\u003c\/p\u003e \u003cp\u003e16.4.3.5 Simulations 449\u003c\/p\u003e \u003cp\u003e16.5 Future Research Challenges and Visions 450\u003c\/p\u003e \u003cp\u003eReferences 451\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Digital Twins and Automation of Care in the Intensive Care Unit 457\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJ. Geoffrey Chase, Cong Zhou, Jennifer L. Knopp, Knut Moeller, Balázs Benyo, Thomas Desaive, Jennifer H. K. Wong, Sanna Malinen, Katharina Naswall, Geoffrey M. Shaw, Bernard Lambermont, and Yeong S. Chiew\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 457\u003c\/p\u003e \u003cp\u003e17.1.1 Economic Context 458\u003c\/p\u003e \u003cp\u003e17.1.2 Healthcare Context 459\u003c\/p\u003e \u003cp\u003e17.1.3 Technology Context 460\u003c\/p\u003e \u003cp\u003e17.1.4 Overall Problem and Need 460\u003c\/p\u003e \u003cp\u003e17.2 Digital Twins and CPHS 461\u003c\/p\u003e \u003cp\u003e17.2.1 Digital Twin\/Virtual Patient Definition 461\u003c\/p\u003e \u003cp\u003e17.2.2 Requirements in an ICU Context 463\u003c\/p\u003e \u003cp\u003e17.2.3 Digital Twin Models in Key Areas of ICU Care and Relative to Requirements 464\u003c\/p\u003e \u003cp\u003e17.2.4 Review of Digital Twins in Automation of ICU Care 466\u003c\/p\u003e \u003cp\u003e17.2.5 Summary 467\u003c\/p\u003e \u003cp\u003e17.3 Role of Social-Behavioral Sciences 467\u003c\/p\u003e \u003cp\u003e17.3.1 Introduction 467\u003c\/p\u003e \u003cp\u003e17.3.2 Barriers to Innovation Adoption 467\u003c\/p\u003e \u003cp\u003e17.3.3 Ergonomics and Codesign 468\u003c\/p\u003e \u003cp\u003e17.3.4 Summary (Key Takeaways) 469\u003c\/p\u003e \u003cp\u003e17.4 Future Research Challenges and Visions 470\u003c\/p\u003e \u003cp\u003e17.4.1 Technology Vision of the Future of CPHS in ICU Care 470\u003c\/p\u003e \u003cp\u003e17.4.2 Social-Behavioral Sciences Vision of the Future of CPHS in ICU Care 471\u003c\/p\u003e \u003cp\u003e17.4.3 Joint Vision of the Future and Challenges to Overcome 473\u003c\/p\u003e \u003cp\u003e17.5 Conclusions 473\u003c\/p\u003e \u003cp\u003eReferences 474\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart V Sociotechnical Systems 491\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Online Attention Dynamics in Social Media 493\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMaria Castaldo, Paolo Frasca, and Tommaso Venturini\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction to Attention Economy and Attention Dynamics 493\u003c\/p\u003e \u003cp\u003e18.2 Online Attention Dynamics 494\u003c\/p\u003e \u003cp\u003e18.2.1 Collective Attention Is Limited 494\u003c\/p\u003e \u003cp\u003e18.2.2 Skewed Attention Distribution 495\u003c\/p\u003e \u003cp\u003e18.2.3 The Role of Novelty 496\u003c\/p\u003e \u003cp\u003e18.2.4 The Role of Popularity 496\u003c\/p\u003e \u003cp\u003e18.2.5 Individual Activity Is Bursty 499\u003c\/p\u003e \u003cp\u003e18.2.6 Recommendation Systems Are the Main Gateways for Information 500\u003c\/p\u003e \u003cp\u003e18.2.7 Change Is the Only Constant 500\u003c\/p\u003e \u003cp\u003e18.3 The New Challenge: Understanding Recommendation Systems Effect in Attention Dynamics 501\u003c\/p\u003e \u003cp\u003e18.3.1 Model Description 502\u003c\/p\u003e \u003cp\u003e18.3.2 Results and Discussion 503\u003c\/p\u003e \u003cp\u003e18.4 Conclusion 505\u003c\/p\u003e \u003cp\u003eAcknowledgments 505\u003c\/p\u003e \u003cp\u003eReferences 505\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Cyber–Physical–Social Systems for Smart City 511\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eGang Xiong, Noreen Anwar, Peijun Ye, Xiaoyu Chen, Hongxia Zhao, Yisheng Lv, Fenghua Zhu, Hongxin Zhang, Xu Zhou, and Ryan W. Liu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction 511\u003c\/p\u003e \u003cp\u003e19.2 Social Community and Smart Cities 513\u003c\/p\u003e \u003cp\u003e19.2.1 Smart Infrastructure 513\u003c\/p\u003e \u003cp\u003e19.2.2 Smart Energy 515\u003c\/p\u003e \u003cp\u003e19.2.3 Smart Transportation 515\u003c\/p\u003e \u003cp\u003e19.2.4 Smart Healthcare 517\u003c\/p\u003e \u003cp\u003e19.3 CPSS Concepts, Tools, and Techniques 518\u003c\/p\u003e \u003cp\u003e19.3.1 CPSS Concepts 518\u003c\/p\u003e \u003cp\u003e19.3.2 CPSS Tools 519\u003c\/p\u003e \u003cp\u003e19.3.3 CPSS Techniques 520\u003c\/p\u003e \u003cp\u003e19.3.3.1 IoT in Smart Cities 520\u003c\/p\u003e \u003cp\u003e19.3.3.2 Big Data in Smart Cities 525\u003c\/p\u003e \u003cp\u003e19.4 Recent Research Advances 528\u003c\/p\u003e \u003cp\u003e19.4.1 Recent Research Advances of CASIA 528\u003c\/p\u003e \u003cp\u003e19.4.2 Recent Research in European Union 531\u003c\/p\u003e \u003cp\u003e19.4.3 Future Research Challenges and Visions 533\u003c\/p\u003e \u003cp\u003e19.5 Conclusions 537\u003c\/p\u003e \u003cp\u003eAcknowledgments 538\u003c\/p\u003e \u003cp\u003eReferences 538\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart VI Concluding Remarks 543\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 Conclusion and Perspectives 545\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAnuradha M. Annaswamy, Pramod P. Khargonekar, Françoise Lamnabhi-Lagarrigue, and Sarah K. Spurgeon\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Benefits to Humankind: Synthesis of the Chapters and their Open Directions 545\u003c\/p\u003e \u003cp\u003e20.2 Selected Areas for Current and Future Development in CPHS 547\u003c\/p\u003e \u003cp\u003e20.2.1 Driver Modeling for the Design of Advanced Driver Assistance Systems 547\u003c\/p\u003e \u003cp\u003e20.2.2 Cognitive Cyber–Physical Systems and CPHS 547\u003c\/p\u003e \u003cp\u003e20.2.3 Emotion–Cognition Interactions 548\u003c\/p\u003e \u003cp\u003e20.3 Ethical and Social Concerns: Few Directions 549\u003c\/p\u003e \u003cp\u003e20.3.1 Frameworks for Ethics 550\u003c\/p\u003e \u003cp\u003e20.3.2 Technical Approaches 550\u003c\/p\u003e \u003cp\u003e20.4 Afterword 551\u003c\/p\u003e \u003cp\u003eReferences 551\u003c\/p\u003e \u003cp\u003eIndex 555\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":48738371666263,"sku":"9781119857402","price":95.4,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119857402.jpg?v=1723811988"},{"product_id":"talking-to-robots-9781472142924","title":"Talking to Robots","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003e''If you want to see what that future might look like, Duncan''s book is a fun place to start''\u003c\/b\u003e\u003cbr\u003eNPR\u003cbr\u003e\u003cbr\u003e\u003cb\u003e''Intensely readable, downright terrifying, and surprisingly uplifting''\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eVanity Fair\u003c\/i\u003e\u003cbr\u003e\u003cbr\u003e \u003cb\u003e''5 books not to miss . . . 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[he] is a popularizer and storyteller. * USA Today *\u003cbr\u003eA riveting read. * Time Magazine *\u003cbr\u003eA brilliant chronicle of encounters with our future selves. -- Andrei Codrescu, bestselling author and NPR commentator\u003cbr\u003e'Intensely readable, downright terrifying, and surprisingly uplifting.' * Vanity Fair *\u003cbr\u003e'A fascinating work of imaginative futurology, a science journalist takes a look at our current technologies and anticipates the human-robot future that could await us - one full of warrior bots, politician bots, doctor bots and sex bots.' -- Barbara VanDenburgh * ‘5 Books Not to Miss’, USA Today *\u003cbr\u003eOne of the best summer reads of 2019. -- David Baldacci and Elizabeth Acevedo * USA Today’s Today programme *\u003c\/p\u003e","brand":"Little, Brown Book Group","offers":[{"title":"Default Title","offer_id":48739393143127,"sku":"9781472142924","price":10.44,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781472142924.jpg?v=1723812231"},{"product_id":"rule-of-the-robots-how-artificial-intelligence-will-transform-everything-9781529345988","title":"Rule of the Robots: How Artificial Intelligence","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003e\u003ci\u003e'\u003c\/i\u003eThe best up-to-date, go-to book on the social and economic implications of artificial intelligence - Tyler Cowen'\u003cbr\u003e\u003c\/b\u003e\u003ci\u003e\u003cb\u003e\u003cbr\u003eRule of the Robots\u003c\/b\u003e \u003c\/i\u003e\u003cb\u003eexplores the future implications of artificial intelligence as a uniquely scalable and potentially disruptive technology.\u003cbr\u003e\u003c\/b\u003e\u003cbr\u003eIn this sequel to his prescient New York Times bestseller \u003ci\u003eRise of the Robots\u003c\/i\u003e, Martin Ford presents us with a striking vision of the very near future. He argues that AI is a uniquely powerful technology, a kind of \"electricity of intelligence\" that is altering every dimension of human life, often for the better with advanced science being done by machines who can solve problems humans can not. AI has the potential to help us fight climate change or the next pandemic, but it also has a capacity for profound harm. Deep fakes-AI-generated audio or video of events that never happened-are poised to cause havoc throughout society. AI empowers authoritarian regimes like China with unprecedented mechanisms for social control. And AI can be deeply biased, learning bigoted attitudes from the data used to train algorithms and perpetuating them. \u003cbr\u003e\u003cbr\u003eHard-hitting and thought-provoking, covering everything from self-driving cars to the history of deep learning to apps for diagnosing skin cancer,\u003ci\u003e Rule of the Robots\u003c\/i\u003e challenges our fears and preconceptions about artificial intelligence. Ford argues that AI is here to stay and the real question is not how to stop it, but how to control its negative potential and harness its power for good as AI transforms our economy, our politics, and our lives.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003eProbably the most compelling single-volume book so far on AI's advance and the opportunities and challenges associated with its multi-faceted impact on the world. Those in AI and those outside it will get a lot out of his clear-eyed and critical perspective. I highly recommend it -- James Manyika, Chairman and Director of the McKinsey Global Institute\u003cbr\u003e\u003cp\u003eThere is no technology more important today than AI. Martin Ford continues his tradition of clear insights and observations about this important topic in a well-researched page-turner. 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Turing Award and co-author of The Book of Why\u003cbr\u003e\u003ci\u003eRule of the Robots \u003c\/i\u003eis subtle and clever, a book that will challenge readers to reassess their position on AI -- Engineering And Technology\u003cbr\u003eAccording to software developer Martin Ford, artificial intelligence (AI) will probably transform society faster than electricity did, but with unpredictable effects. His well-informed study notes a 2016 forecast that within five years, radiologists would be overtaken by advances in AI. But that hasn't happened: AI cannot currently integrate key information from sources such as clinical notes. AI's future, Ford concludes, lies somewhere between the science-fictional extremes of utopian \u003ci\u003eStar Trek\u003c\/i\u003e and dystopian \u003ci\u003eThe Matrix\u003c\/i\u003e -- Nature\u003cbr\u003eA good read and . . . a balanced perspective on both the benefits and costs of increasingly widespread use of AI -- Diane Coyle, Enlightenment Economics","brand":"John Murray Press","offers":[{"title":"Default Title","offer_id":48740199661911,"sku":"9781529345988","price":17.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781529345988.jpg?v=1723812290"},{"product_id":"make-volume-58-9781680453622","title":"Make: Volume 58","description":"\u003cp\u003e\u003c\/p\u003e\u003cp\u003eDo It Together!\u003cbr\u003e\u003cbr\u003eMaking is better when you're doing it with friends! 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You will learn how AI is being utilised today to support products, services, science and engineering, and how it is likely to be used in the future to balance the talents of humans and machines. You will explore robotics and machine learning within the context of AI, and discover how the challenges AI presents are being addressed. You will delve into the theory behind AI and machine learning projects, examining techniques for learning from data, the use of neural networks and why algorithms are so important in the development of a new AI agent or system.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e'This book is a welcome read for those who want to know more about AI but don’t have a degree level background in the underlying subjects.  It successfully brings the beginner up to speed and is written with such enthusiasm that the more complex topics become manageable.  For a foundation level book it covers an impressive content range, whilst also providing a solid grounding in Machine Learning. The topics are clearly and succinctly exemplified by 3 case studies which bring AI into the real world.' -- Rosie Sheldon * Senior Trainer, TSG-training *\u003cbr\u003e'Many commentators see AI as the key enabler of the fifth industrial revolution.  In this clear and concise guide to the BCS Artificial Intelligence Foundation qualification, Andrew Lowe and Steve Lawless set out to clearly explain the core concepts around artificial intelligence, machine learning, applications in robotics and more.  A ‘must have’ guide in preparation for the BCS AI Foundation exam, this book will not only assist with exam success, but will capture your imagination to the possibilities in front of us when reimagining the human vs machine relationship.' -- Richard Webber * Digital Transformation Programme Manager, Ravensbourne University London *\u003cbr\u003e'This is a great book for executives to understand how AI may fit into their company and the types of benefits that they may gain and some of the pitfalls they may fall into. The book gives a clear picture of where AI fits with other types of decision-making processes. It covers many different aspects of how AI can be developed and how it affects society, with a particular focus on ethics and the human machine interface.' -- Dr Paul Edward Mort, B.Eng. (Hons), PhD, MBA, MIMechE CEng FNucI * Innovation Lead for Special Nuclear Materials, Sellafield Ltd *\u003cbr\u003e'Produces a great storm of ideas and thoughts with a funny touch from the authors...This is a piece of art and a “must read\", for good immersion in the theme.' -- David Mondragón Tapia * IT \u0026amp; Business Consultant, DieresiS - Business and Professional Services *\u003cbr\u003e'This book is a highly recommended read for those starting out on Artificial Intelligence learning or as a refresher, written by two very knowledgeable authors, who put across the subject in an easy to understand manner.' -- Mat Gardam * Cyber Security Professional *\u003cbr\u003e'Manages to provide a fundamental grounding in the theory and application of AI without relying on mathematical or data science skills...the theory is colourfully illustrated with examples of both AI successes and challenges, which will prove an invaluable foundation to the reader's learning from experience in the world of Artificial Intelligence.' -- Mark Ainsworth * Director and Business Analyst, Promising ICT Limited *\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003col\u003e\n\u003cli\u003eIntroduction - Ethical and Sustainable Human and Artificial AI\u003c\/li\u003e\n\u003cli\u003eArtificial Intelligence and Robotics\u003c\/li\u003e\n\u003cli\u003eApplying The Benefits of AI and Identifying Challenges and Risks\u003c\/li\u003e\n\u003cli\u003eStarting AI - How to Build A Machine Learning Toolbox\u003c\/li\u003e\n\u003cli\u003eAlgorithms \u003c\/li\u003e\n\u003cli\u003eThe Management, Roles and Responsibilities of Humans and Machines\u003c\/li\u003e\n\u003cli\u003eAI in Use in Industry - Reimagining Everything in the Fourth Industrial Revolution\u003c\/li\u003e\n\u003cli\u003eAI Case Studies \u003c\/li\u003e\n\u003c\/ol\u003e","brand":"BCS Learning \u0026 Development Limited","offers":[{"title":"Default Title","offer_id":48740982915415,"sku":"9781780175287","price":33.24,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781780175287.jpg?v=1720056211"},{"product_id":"gravity-compensation-in-robotics-9783030957490","title":"Gravity Compensation in Robotics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis book presents new research results in the field of gravity compensation in robotic systems. It explores topics such as gravity compensation of planar articulated robotic manipulators; the stiffness modeling of manipulators with gravity compensators; the multi-degree-of-freedom counter-balancing; the design of actuators with partial gravity compensation; a cable-driven robotic suit with gravity compensation for load carriage; various compensation systems for medical cobots and assistive devices; gravity balancing of parallel robots.\u003c\/p\u003e  \u003cp\u003eThe volume demonstrates that gravity compensation methods continue to develop, and new approaches and solutions are constantly being reported. These solutions apply both to new structural solutions and to their new applications. 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This book allows such a brain to tell us how it takes on its mission of helping humans to develop a more efficient, sustainable, diverse and inclusive society.\u003cbr\u003e\u003cbr\u003eThis book explains the principles and applications of artificial intelligence for a broad audience. Artificial intelligence, as part of computer science, is often inspired by human intelligence. At the same time, there is still reluctance in the applications and usability of artificial intelligence among citizens. Industries are deploying AI in their products and processes but the level of maturity is varying. 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In particular, the Robot Operating System (ROS) offers a unified platform that greatly facilitates the development of robots and has become a new hotspot for learning and application in the field of robotics research.This book introduces readers to the key technologies and development methods for ROS-based intelligent robots. Covering both the development history of robots and various aspects of programming robots, it offers effective support for beginners.The book is divided into three parts, the first of which introduces the basics of robots, including their definition, development, composition, and key technologies. In turn, the second part covers the hardware and software components and the implementation of functions such as vision, speech, grasping, and autonomous navigation. These functions need to work together to provide user-friendlier and more intelligent service. The third part shows how to develop robots with different functions in different application scenarios.Combining theoretical and practical aspects, with a strong focus on application, this work can be used as a reference book for robotics-related courses. Moreover, it will benefit all readers who are interested in intelligent robot development, sharing essential insights into developing service robots based on ROS.\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e“The book is an effective tutorial for using ROS. So embark on reading it if you intend to adopt ROS, either by delivering your software or for using available software on your robot.” (G. Gini, Computing Reviews, July 17, 2023)\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eChapter 1 Introduction to Robots.- Chapter 2 Getting Started with ROS.- Chapter 3 The framework of ROS.- Chapter 4 Programming with ROS.- Chapter 5 Introduction to Turtlebot Robot .- Chapter 6 Robot Vision: Theory and Implementation.- Chapter 7 Advanced Robot Vision.- Chapter 8 Robot Autonomous Navigation: Theory and Implementation.- Chapter 9 Robot Speech: Theory and Implementation.- Chapter 10 Robotic Hands, Grasping and Manipulation.- Chapter 11 Case 1: Long command recognition and multi-task execution.- Chapter 12 Case 2: Follow and assist the user.- Chapter 13 Case 3: Restaurant scenario: wave hand to order food.\u003c\/p\u003e","brand":"Springer Verlag, Singapore","offers":[{"title":"Default Title","offer_id":48743293649239,"sku":"9789811982521","price":52.24,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9789811982521.jpg?v=1723812658"},{"product_id":"the-science-of-soft-robots-design-materials-and-information-processing-9789811951732","title":"The Science of Soft Robots: Design, Materials and","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThe goal of this textbook is to equip readers with as structured knowledge of soft robotics as possible. Seeking to overcome the limitations of conventional robots by making them more flexible, gentle and adaptable, soft robotics has become one of the most active fields over the last decade. Soft robotics is also highly interdisciplinary, bringing together robotics, computer science, material science, biology, etc.\u003c\/p\u003e  \u003cp\u003eAfter the introduction, the content is divided into three parts: Design of Soft Robots; Soft Materials; and Autonomous Soft Robots. Part I addresses soft mechanisms, biological mechanisms, and soft manipulation \u0026amp; locomotion. In Part II, the basics of polymer, biological materials, flexible \u0026amp; stretchable sensors, and soft actuators are discussed from a materials science standpoint. In turn, Part III focuses on modeling \u0026amp; control of continuum bodies, material intelligence, and information processing using soft body dynamics. 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Versus a ?punch?? Should robots reach out to a human counterpart with a direct, telescoping action or through a circuitous arc in space? Just as different movements express the different internal states of human movers, so too can the engineered systems behind robots. In \u003ci\u003eMaking Meaning with Machines\u003c\/i\u003e, Amy LaViers and Catherine Maguire offer a refreshingly embodied approach to machine design that supports the growing need to make meaning with machines by using the field of movement studies, including choreography, somatics, and notation, to engage in the process of designing expressive robots.\u003cbr\u003e\u003cbr\u003eDrawing upon the Laban\/Bartenieff tradition, LaViers and Maguire sharpen the movement analysis methodology, expanding the material through their work with machines and putting forward new conventions, such as capitalization, naming, and notation schemes, that make the embodied work more legible for academic contexts. The book includes an overview of movement studies, exercises that define the presented taxonomy and principles of movement, case studies in movement analysis of both humans and robots, and state-of-the-art research at the intersection of robotics and dance.\u003cbr\u003e\u003cbr\u003e\u003ci\u003eMaking Meaning with Machines\u003c\/i\u003e is a much-needed primer for observing, describing, and creating a wide array of movement patterns, which ultimately can help facilitate broader and better design choices for roboticists, technologists, and designers.","brand":"MIT Press Ltd","offers":[{"title":"Default Title","offer_id":48864306921815,"sku":"9780262546126","price":54.15,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780262546126.jpg?v=1722271326"},{"product_id":"person-thing-robot-9780262546157","title":"Person Thing Robot","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"MIT Press","offers":[{"title":"Default Title","offer_id":48864307052887,"sku":"9780262546157","price":40.85,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780262546157.jpg?v=1722271327"},{"product_id":"ai-2041-9780753559024","title":"AI 2041","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003eKai-Fu Lee (Author) \u003c\/b\u003e\u003cbr\u003e\u003cb\u003eKai-Fu Lee\u003c\/b\u003e is the CEO of Sinovation Ventures and \u003ci\u003eNew York Times\u003c\/i\u003e bestselling author of \u003ci\u003eAI Superpowers\u003c\/i\u003e. Lee was formerly the president of Google China and a senior executive at Microsoft, SGI, and Apple. Co-chair of the Artificial Intelligence Council at the World Economic Forum, he has a bachelor's degree from Columbia and a PhD from Carnegie Mellon. Lee's numerous honors include being named to the \u003ci\u003eTime\u003c\/i\u003e 100 and \u003ci\u003eWired\u003c\/i\u003e 25 Icons lists.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eChen Qiufan (Author) \u003c\/b\u003e\u003cbr\u003e\u003cb\u003eChen Qiufan (aka Stanley Chan) \u003c\/b\u003eis an award-winning author, translator, creative producer, and curator. He is the president of the World Chinese Science Fiction Association. His works include \u003ci\u003eWaste Tide, Future Diseases, \u003c\/i\u003eand\u003ci\u003e The Algorithm for Life.\u003c\/i\u003e The founder of Thema Mundi, a content development studio, he lives in Beijing and Shanghai.\u003c\/p\u003e","brand":"Ebury Publishing","offers":[{"title":"Default Title","offer_id":48865769259351,"sku":"9780753559024","price":11.69,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780753559024.jpg?v=1722275477"},{"product_id":"robots-wont-save-japan-9781501768040","title":"Robots Wont Save Japan","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThe title says it all, really, Robots Won't Save Japan, but do read the book if you want to be convinced, because you will be. The author, anthropologist and science and technology studies (STS) scholar James Wright, has adopted this title in reaction to a Japanese book from a generation ago, Robots Will Save Japan (Nakayama 2006).\u003c\/p\u003e * Anthropology \u0026amp; Aging *\u003cbr\u003e\u003cp\u003eRobots Won't Save Japan is a vivid example for how ethnographic research can enrich and deepen our understanding of complex social and political problems\u003c\/p\u003e * Contemporary Japan *\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eIntroduction\u003cbr\u003e 1. Crisis and Care Robots\u003cbr\u003e 2. Developing Robots and Designing Algorithmic Care\u003cbr\u003e 3. Portrait of a Care Home\u003cbr\u003e 4. Hug: Reconfiguring Lifting\u003cbr\u003e 5. Paro: Reconfiguring Communication\u003cbr\u003e 6. Pepper: Reconfiguring Recreation\u003cbr\u003e 7. Beyond Care Robots\u003c\/p\u003e","brand":"Cornell University Press","offers":[{"title":"Default Title","offer_id":48867347431767,"sku":"9781501768040","price":37.05,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781501768040.jpg?v=1722282909"},{"product_id":"scary-smart-the-future-of-artificial-intelligence-and-how-you-can-save-our-world-9781529077650","title":"Scary Smart: The Future of Artificial","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003eA\u003ci\u003e Sunday Times \u003c\/i\u003eBusiness Book of the Year.\u003cbr\u003e\u003cbr\u003e\u003ci\u003eScary Smart\u003c\/i\u003e will teach you how to navigate the scary and inevitable intrusion of Artificial Intelligence, with an accessible blueprint for creating a harmonious future alongside AI. From Mo Gawdat, the former Chief Business Officer at Google [X] and bestselling author of \u003ci\u003eSolve for Happy.\u003c\/i\u003e\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\u003ci\u003eTechnology is putting our humanity at risk to an unprecedented degree. This book is not for engineers who write the code or the policy makers who claim they can regulate it. This is a book for you. Because, believe it or not, you are the only one that can fix it.\u003c\/i\u003e – Mo Gawdat\u003cbr\u003e\u003cbr\u003eArtificial intelligence is smarter than humans. It can process information at lightning speed and remain focused on specific tasks without distraction. AI can see into the future, predict outcomes and even use sensors to see around physical and virtual corners. So why does AI frequently get it so wrong and cause harm?\u003cbr\u003e\u003cbr\u003eThe answer is us: the human beings who write the code and teach AI to mimic our behaviour. \u003ci\u003eScary Smart\u003c\/i\u003e explains how to fix the current trajectory now, to make sure that the AI of the future can preserve our species. This book offers a blueprint, pointing the way to what we can do to safeguard ourselves, those we love, and the planet itself.\u003cbr\u003e\u003cbr\u003e\u003cb\u003e'No one ever regrets reading anything Mo Gawdat has written.' – Emma Gannon, author of \u003ci\u003eThe Multi-Hyphen Method\u003c\/i\u003e and host of the podcast \u003ci\u003eCtrl Alt Delete\u003c\/i\u003e\u003c\/b\u003e\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003eMo Gawdat is my life guru. His writing, his ideas and his generosity in sharing them has changed my life for the better in so many ways. Everything he writes is an enlightening education in how to be human. -- \u003cb\u003eElizabeth Day\u003c\/b\u003e\u003cbr\u003eMo is an exquisite writer and speaker with deep expertise of technology . . . This book will teach you how to navigate the scary and inevitable intrusion of AI as well as who really is in control. Us. -- \u003cb\u003eDr Rupy Aujla, MBBS, BSc, MRCGP, Founder of \"The Doctor's Kitchen\"\u003c\/b\u003e\u003cbr\u003eA proactive and bold read that provides the shake that humans need to take back our agency over AI, and therefore the fate of the world as we see it. -- \u003cb\u003eDr Camilla Pang, author of \u003ci\u003eExplaining Humans: What Science Can Teach Us About Life, Love and Relationships\u003c\/i\u003e\u003c\/b\u003e\u003cbr\u003eA brilliant mind . . . Mo takes us on a whirlwind exploration of the fast-approaching singularity, and offers a desperate last chance to have a say in the future of humanity. Read this book! -- \u003cb\u003eTim Ash, bestselling author of \u003ci\u003eUnleash Your Primal Brain\u003c\/i\u003e\u003c\/b\u003e\u003cbr\u003eNo one ever regrets reading anything Mo Gawdat has written. -- \u003cb\u003eEmma Gannon, \u003ci\u003eSunday Times \u003c\/i\u003ebestselling author of \u003ci\u003eThe Multi-Hyphen Method \u003c\/i\u003eand host of award-winning podcast \u003ci\u003eCtrl Alt Delete\u003c\/i\u003e\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eScary Smart\u003c\/i\u003e is unlike anything I’ve ever read . . . 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You'll be introduced to simple DIY electronics and Arduino programming, and you will learn how to use those tools to create a treasure trove of magic bots and effects, with readily-sourced materials and everyday objects. It's magic through the lens of the Maker Movement, with a dedication to accessibility -- cardboard meets Arduino meets magic! All ages, backgrounds, and abilities will find clever, fun projects within these pages that challenge their creativity and explode their imagination.","brand":"O'Reilly Media","offers":[{"title":"Default Title","offer_id":48868032774487,"sku":"9781680457124","price":16.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781680457124.jpg?v=1722286104"},{"product_id":"the-official-raspberry-pi-handbook-astounding-projects-with-raspberry-pi-computers-2024-9781912047338","title":"The Official Raspberry Pi Handbook: Astounding","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThe Official Raspberry Pi Handbook is fully updated for Raspberry Pi in 2024. Packed with all the information beginners need to use their new Raspberry Pi computer. And the best projects from the year for long-term Raspberry Pi enthusiasts.  Learn how to set up the Raspberry Pi, install an operating system, and start using Raspberry Pi OS. Follow step-by-step guides to code animations and games using both Scratch and Python languages. Create incredible computing projects with electronic components.  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The introduction of the profound significance of the robots and delineation of the navigation and routing theme is provided in the first chapter of the book. The second chapter is concerned with the subject of routing in unknown environments. In the first part of this chapter, the family of bug algorithms including are described. In the following, several conventional methods are submitted. The last part of this chapter is dedicated to the introduction of two recently developed routing methods. In Chapter 3, routing is reviewed in the known environment in which the robot either utilizes the created maps by extraneous sources or makes use of the sensor in order to prepare the maps from the local environment. The robot path planning relying on the robot vision sensors and applicable computing hardware are concentrated in the fourth chapter. The first part of this chapter deals with routing methods supported mapping capabilities. The second part manages the routing dependent on the vision sensor, typically known as the best sensor, within the routing subject. The movement of two-dimensional robots with two or three degrees of freedom is analyzed within the third part of this chapter. In Chapter 5, the performance of a few of the foremost important routing methods initiating from the second to fourth chapters is conferred regarding the implementation in various environments. The first part of this chapter is engaged in the implementation of the algorithms Bug1, Bug2, and Distbug on the pioneering robot. In the second part, a theoretical technique is planned to boost the robot's performance in line with obstacle collision avoidance. This method, underlying the tangential escape, seeks to proceed with the robot through various obstacles with curved corners. In the third and fourth parts of this chapter, path planning in different environments is preceded in the absence and the presence of danger space. 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The tendency in Industry 4.0 towards the mass customisation of products, shorter product cycles and quality demands has led to the introduction of collaborative robot's systems capable of learning and working hand-in-hand with humans. Collaborative robots in the industry target the enhancement of production efficiency by combining the best of human operators and the industrial robots' accuracy, speed and reliability. The advances in smart sensors, artificial intelligence, digital twin, cyber-physical systems and the adoption of exoskeletons in industrial applications have opened new possibilities for technological progress in manufacturing, which led to efficient and flexible factories. This requires individuals to be educated in trends that are now focused on the design, monitoring and control of smart production processes. Featuring coverage on a wide range of topics such as new trends in human-robot collaboration, advanced vision technology and artificial intelligence, as well as application of industry robots in metal and wood industry, this book is ideally designed for electrical engineers, mechanical engineers, manufacturers, supply chain managers, logistics specialists, investors, managers, policymakers, production scientists, researchers, academicians and students at the postgraduate level.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePreface; The Application of Robots in the Industry; Industrial Robot Systems and Classifications; Sensors in Robotics; 3D Robotic Vision; Robot Vision in Industrial Applications; Robot Actuators; Kinematics and Dynamics of Robots; Collaborative Robots: Overview and Future Trends; Artificial Intelligence Driving Advances in Human-Robot Collaboration; The Study on Key Technologies of Collaborative Robot, Sensorless Applications and Extenstions; The Application of Robots in the Metal Industry; The Implementation of Robots in Wood Industry; Human Grasping as an Archetype of Grasping in Robotics: New Contributions in Premises, Experimentation and Mathematical Modeling; Application of Industrial Robots for Robotic Machining; Index.","brand":"Nova Science Publishers Inc","offers":[{"title":"Default Title","offer_id":48886169960791,"sku":"9781536177794","price":999.99,"currency_code":"GBP","in_stock":false}]},{"product_id":"a-closer-look-at-formation-control-9781536181777","title":"A Closer Look at Formation Control","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eFormation control is one of the most challenging problems in cooperative multi-robots. It is defined as a coordination of a group of robots to get into and to maintain a formation with a certain shape. The formation control problem has drawn significant attention for many years, and now it is well understood and tends to be mature. This control problem is originated from biological inspires such as flocking and schooling. Its classification includes formation shape generation, formation reconfiguration and selection, formation tracking, and role assignment in formation. It also has potential applications in search and rescue missions, forest fire detection and surveillance, etc. It can be extended to many real-world systems, autonomous robots, such as underwater vehicles, unmanned aerial vehicles, mobile sensor networks, rectangular agents, nonholonomic mobile robots, to name but a few. Apparently, the book cannot include all research topics. The editor and the authors wish that it could reveal some tendencies on this research field and benefit readers. 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Chapters includes some new tendencies and developments in research on several formation methods of multi-robot systems, that is, the 1st-order sliding mode control, the 2nd-order sliding mode control, the integral sliding mode control, the terminal sliding mode control, the sliding model control of multi-agents and the fuzzy-based formation control of multiple quadrotor systems.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePreface; Modelling of Leader-Follower Formations; 1st-Order Sliding Mode-Based Formation Design; Coordinated Formation via an Adaptive-Gain 2nd-Order Sliding Mode Method; Integral Sliding Mode-Based Formation Maneuvers of Multi-Agent Robots; Leader-Following Formation Control of Multiple Agents via Derivative and Integral Terminal Sliding Mode; Extreme Learning Machine-Based Sliding Mode Formation Maneuvers for Multi-Robot Systems; Formation Design of Multiple Agents with Uncertainties by Integral Sliding Mode; A Fuzzy Logic-Based Adaptive Strictly Negative-Imaginary Formation Controller for Multi-Quadrotor Systems; Index.","brand":"Nova Science Publishers Inc","offers":[{"title":"Default Title","offer_id":48886177628503,"sku":"9781536181777","price":113.59,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781536181777.jpg?v=1722539099"},{"product_id":"robotics-a-bibliography-with-indexes-9781590332962","title":"Robotics: A Bibliography with Indexes","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eRobotics has worked its way from science fiction to science without the fiction to widespread applications not only in manufacturing but in medical research and other fields as well. Progress had been accelerated by the faster-than-light advances in miniaturisation. This book provides important citations, primarily to the book literature, with access through author, subject and title indexes.","brand":"Nova Science Publishers Inc","offers":[{"title":"Default Title","offer_id":48886469591383,"sku":"9781590332962","price":999.99,"currency_code":"GBP","in_stock":false}]},{"product_id":"focus-on-robotics-research-9781594545948","title":"Focus on Robotics Research","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eRobotics began as a science fiction creation which has become quite real, first in assembly line operations such as automobile manufacturing, aeroplane construction etc. They have now reached such areas as the internet, ever-multiplying-medical uses and sophisticated military applications. Control of today''s robots is often remote which requires even more advanced computer vision capabilities as well as sensors and interface techniques. Learning has become crucial for modern robotic systems as well. This book brings together leading research in this exciting field.","brand":"Nova Science Publishers Inc","offers":[{"title":"Default Title","offer_id":48886524805463,"sku":"9781594545948","price":173.24,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781594545948.jpg?v=1722540453"},{"product_id":"frontiers-in-robotics-research-9781600210976","title":"Frontiers in Robotics Research","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eRobotics began as a science fiction creation which has become quite real, first in assembly line operations such as automobile manufacturing, aeroplane construction etc. They have now reached such areas as the internet, ever-multiplying-medical uses and sophisticated military applications. 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Learning has become crucial for modern robotic systems as well. This book presents the latest research in the field.","brand":"Nova Science Publishers Inc","offers":[{"title":"Default Title","offer_id":48886613475671,"sku":"9781600219979","price":999.99,"currency_code":"GBP","in_stock":false}]},{"product_id":"robot-vision-new-research-9781604569841","title":"Robot Vision: New Research","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThe field of robot vision guidance is developing rapidly. The benefits of sophisticated vision technology include savings, improved quality, reliability, safety and productivity. Robot vision is used for part identification and navigation. Vision applications generally deal with finding a part and orienting it for robotic handling or inspection before an application is performed. Sometimes vision guided robots can replace multiple mechanical tools with a single robot station. A combination of vision algorithms, calibration, temperature software, and cameras provide the vision ability. Calibration of robot vision system is very application dependent. They can range from a simple guidance application to a more complex application that uses data from multiple sensors. Algorithms are consistently improving, allowing for sophisticated detection. Many robots are now available with collision detection, allowing them to work alongside other robots without the fear of a major collision. They simply stop moving momentarily if they detect another object in their motion path. 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The authors of the second chapter offer an analysis of the dimensions surrounding this argument.","brand":"Nova Science Publishers Inc","offers":[{"title":"Default Title","offer_id":48887237214551,"sku":"9781634851039","price":67.14,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781634851039.jpg?v=1722543631"},{"product_id":"robotics-new-research-9781634859677","title":"Robotics: New Research","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"Nova Science Publishers Inc","offers":[{"title":"Default Title","offer_id":48887252320599,"sku":"9781634859677","price":148.79,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781634859677.jpg?v=1722543693"},{"product_id":"3d-printers-and-additive-manufacturing-the-rise-of-industry-4-0-9781695364981","title":"3D Printers and Additive Manufacturing: The rise","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"Independently Published","offers":[{"title":"Default Title","offer_id":48887507485015,"sku":"9781695364981","price":11.98,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781695364981.jpg?v=1722544898"},{"product_id":"knowledge-management-and-web-3-0-next-generation-business-models-9783110722642","title":"Knowledge Management and Web 3.0: Next Generation","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"De Gruyter","offers":[{"title":"Default Title","offer_id":48889048465751,"sku":"9783110722642","price":95.62,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783110722642.jpg?v=1722552438"},{"product_id":"healthcare-big-data-analytics-9783110750737","title":"Healthcare Big Data Analytics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book highlights how optimized big data applications can be used for patient monitoring and clinical diagnosis. 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