{"product_id":"robot-modeling-and-control-isbn-9781119523994","title":"Robot Modeling and Control","description":"\u003cp\u003e\u003cb\u003eA New Edition Featuring Case Studies and Examples of the Fundamentals of Robot Kinematics, Dynamics, and Control\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIn the 2nd Edition of \u003ci\u003eRobot Modeling and Control\u003c\/i\u003e, students will cover the theoretical fundamentals and the latest technological advances in robot kinematics. With so much advancement in technology, from robotics to motion planning, society can implement more powerful and dynamic algorithms than ever before. This in-depth reference guide educates readers in four distinct parts; the first two serve as a guide to the fundamentals of robotics and motion control, while the last two dive more in-depth into control theory and nonlinear system analysis.\u003c\/p\u003e \u003cp\u003eWith the new edition, readers gain access to new case studies and thoroughly researched information covering topics such as: \u003c\/p\u003e \u003cp\u003e●      Motion-planning, collision avoidance, trajectory optimization, and control of robots\u003c\/p\u003e \u003cp\u003e●      Popular topics within the robotics industry and how they apply to various technologies\u003c\/p\u003e \u003cp\u003e●      An expanded set of examples, simulations, problems, and case studies\u003c\/p\u003e \u003cp\u003e●      Open-ended suggestions for students to apply the knowledge to real-life situations\u003c\/p\u003e \u003cp\u003eA four-part reference essential for both undergraduate and graduate students, \u003ci\u003eRobot Modeling and Control\u003c\/i\u003e serves as a foundation for a solid education in robotics and motion planning.\u003c\/p\u003e \u003cp\u003ePreface v\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Mathematical Modeling of Robots 5\u003c\/p\u003e \u003cp\u003e1.1.1 Symbolic Representation of Robot Manipulators 5\u003c\/p\u003e \u003cp\u003e1.1.2 The Configuration Space 5\u003c\/p\u003e \u003cp\u003e1.1.3 The State Space 6\u003c\/p\u003e \u003cp\u003e1.1.4 The Workspace 7\u003c\/p\u003e \u003cp\u003e1.2 Robots as Mechanical Devices 7\u003c\/p\u003e \u003cp\u003e1.2.1 Classification of Robotic Manipulators 8\u003c\/p\u003e \u003cp\u003e1.2.2 Robotic Systems 10\u003c\/p\u003e \u003cp\u003e1.2.3 Accuracy and Repeatability 10\u003c\/p\u003e \u003cp\u003e1.2.4 Wrists and End Effectors 12\u003c\/p\u003e \u003cp\u003e1.3 Common Kinematic Arrangements 13\u003c\/p\u003e \u003cp\u003e1.3.1 Articulated Manipulator (RRR) 13\u003c\/p\u003e \u003cp\u003e1.3.2 Spherical Manipulator (RRP) 14\u003c\/p\u003e \u003cp\u003e1.3.3 SCARA Manipulator (RRP) 14\u003c\/p\u003e \u003cp\u003e1.3.4 Cylindrical Manipulator (RPP) 15\u003c\/p\u003e \u003cp\u003e1.3.5 Cartesian Manipulator (PPP) 15\u003c\/p\u003e \u003cp\u003e1.3.6 Parallel Manipulator 18\u003c\/p\u003e \u003cp\u003e1.4 Outline of the Text 18\u003c\/p\u003e \u003cp\u003e1.4.1 Manipulator Arms 18\u003c\/p\u003e \u003cp\u003e1.4.2 Underactuated and Mobile Robots 27\u003c\/p\u003e \u003cp\u003eProblems 27\u003c\/p\u003e \u003cp\u003eNotes and References 29\u003c\/p\u003e \u003cp\u003e\u003cb\u003eI The Geometry of Robots 33\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Rigid Motions 35\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Representing Positions 36\u003c\/p\u003e \u003cp\u003e2.2 Representing Rotations 38\u003c\/p\u003e \u003cp\u003e2.2.1 Rotation in the Plane 38\u003c\/p\u003e \u003cp\u003e2.2.2 Rotations in Three Dimensions 41\u003c\/p\u003e \u003cp\u003e2.3 Rotational Transformations 44\u003c\/p\u003e \u003cp\u003e2.4 Composition of Rotations 48\u003c\/p\u003e \u003cp\u003e2.4.1 Rotation with Respect to the Current Frame 48\u003c\/p\u003e \u003cp\u003e2.4.2 Rotation with Respect to the Fixed Frame 50\u003c\/p\u003e \u003cp\u003e2.4.3 Rules for Composition of Rotations 51\u003c\/p\u003e \u003cp\u003e2.5 Parameterizations of Rotations 52\u003c\/p\u003e \u003cp\u003e2.5.1 Euler Angles 53\u003c\/p\u003e \u003cp\u003e2.5.2 Roll, Pitch, Yaw Angles 55\u003c\/p\u003e \u003cp\u003e2.5.3 Axis-Angle Representation 57\u003c\/p\u003e \u003cp\u003e2.5.4 Exponential Coordinates 59\u003c\/p\u003e \u003cp\u003e2.6 Rigid Motions 61\u003c\/p\u003e \u003cp\u003e2.6.1 Homogeneous Transformations 62\u003c\/p\u003e \u003cp\u003e2.6.2 Exponential Coordinates for General Rigid Motions 65\u003c\/p\u003e \u003cp\u003e2.7 Chapter Summary 65\u003c\/p\u003e \u003cp\u003eProblems 67\u003c\/p\u003e \u003cp\u003eNotes and References 73\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Forward Kinematics 75\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Kinematic Chains 75\u003c\/p\u003e \u003cp\u003e3.2 The Denavit-Hartenberg Convention 78\u003c\/p\u003e \u003cp\u003e3.2.1 Existence and Uniqueness 80\u003c\/p\u003e \u003cp\u003e3.2.2 Assigning the Coordinate Frames 83\u003c\/p\u003e \u003cp\u003e3.3 Examples 87\u003c\/p\u003e \u003cp\u003e3.3.1 Planar Elbow Manipulator 87\u003c\/p\u003e \u003cp\u003e3.3.2 Three-Link Cylindrical Robot 89\u003c\/p\u003e \u003cp\u003e3.3.3 The Spherical Wrist 90\u003c\/p\u003e \u003cp\u003e3.3.4 Cylindrical Manipulator with Spherical Wrist 91\u003c\/p\u003e \u003cp\u003e3.3.5 Stanford Manipulator 93\u003c\/p\u003e \u003cp\u003e3.3.6 SCARA Manipulator 95\u003c\/p\u003e \u003cp\u003e3.4 Chapter Summary 96\u003c\/p\u003e \u003cp\u003eProblems 96\u003c\/p\u003e \u003cp\u003eNotes and References 99\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Velocity Kinematics 101\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Angular Velocity: The Fixed Axis Case 102\u003c\/p\u003e \u003cp\u003e4.2 Skew-Symmetric Matrices 103\u003c\/p\u003e \u003cp\u003e4.2.1 Properties of Skew-Symmetric Matrices 104\u003c\/p\u003e \u003cp\u003e4.2.2 The Derivative of a Rotation Matrix 105\u003c\/p\u003e \u003cp\u003e4.3 Angular Velocity: The General Case 107\u003c\/p\u003e \u003cp\u003e4.4 Addition of Angular Velocities 108\u003c\/p\u003e \u003cp\u003e4.5 Linear Velocity of a Point Attached to a Moving Frame 110\u003c\/p\u003e \u003cp\u003e4.6 Derivation of the Jacobian 111\u003c\/p\u003e \u003cp\u003e4.6.1 Angular Velocity 112\u003c\/p\u003e \u003cp\u003e4.6.2 Linear Velocity 113\u003c\/p\u003e \u003cp\u003e4.6.3 Combining the Linear and Angular Velocity Jacobians 115\u003c\/p\u003e \u003cp\u003e4.7 The Tool Velocity 119\u003c\/p\u003e \u003cp\u003e4.8 The Analytical Jacobian 121\u003c\/p\u003e \u003cp\u003e4.9 Singularities 122\u003c\/p\u003e \u003cp\u003e4.9.1 Decoupling of Singularities 123\u003c\/p\u003e \u003cp\u003e4.9.2 Wrist Singularities 125\u003c\/p\u003e \u003cp\u003e4.9.3 Arm Singularities 125\u003c\/p\u003e \u003cp\u003e4.10 Static Force\/Torque Relationships 129\u003c\/p\u003e \u003cp\u003e4.11 Inverse Velocity and Acceleration 131\u003c\/p\u003e \u003cp\u003e4.12 Manipulability 133\u003c\/p\u003e \u003cp\u003e4.13 Chapter Summary 136\u003c\/p\u003e \u003cp\u003eProblems 138\u003c\/p\u003e \u003cp\u003eNotes and References 140\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Inverse Kinematics 141\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 The General Inverse Kinematics Problem 141\u003c\/p\u003e \u003cp\u003e5.2 Kinematic Decoupling 143\u003c\/p\u003e \u003cp\u003e5.3 Inverse Position: A Geometric Approach 145\u003c\/p\u003e \u003cp\u003e5.3.1 Spherical Configuration 146\u003c\/p\u003e \u003cp\u003e5.3.2 Articulated Configuration 148\u003c\/p\u003e \u003cp\u003e5.4 Inverse Orientation 151\u003c\/p\u003e \u003cp\u003e5.5 Numerical Inverse Kinematics 156\u003c\/p\u003e \u003cp\u003e5.6 Chapter Summary 158\u003c\/p\u003e \u003cp\u003eProblems 160\u003c\/p\u003e \u003cp\u003eNotes and References 162\u003c\/p\u003e \u003cp\u003e\u003cb\u003eII Dynamics and Motion Planning 163\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Dynamics 165\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 The Euler-Lagrange Equations 166\u003c\/p\u003e \u003cp\u003e6.1.1 Motivation 166\u003c\/p\u003e \u003cp\u003e6.1.2 Holonomic Constraints and Virtual Work 170\u003c\/p\u003e \u003cp\u003e6.1.3 D'Alembert's Principle 174\u003c\/p\u003e \u003cp\u003e6.2 Kinetic and Potential Energy 177\u003c\/p\u003e \u003cp\u003e6.2.1 The Inertia Tensor 178\u003c\/p\u003e \u003cp\u003e6.2.2 Kinetic Energy for an \u003ci\u003en\u003c\/i\u003e-Link Robot 180\u003c\/p\u003e \u003cp\u003e6.2.3 Potential Energy for an \u003ci\u003en\u003c\/i\u003e-Link Robot 181\u003c\/p\u003e \u003cp\u003e6.3 Equations of Motion 181\u003c\/p\u003e \u003cp\u003e6.4 Some Common Configurations 184\u003c\/p\u003e \u003cp\u003e6.5 Properties of Robot Dynamic Equations 194\u003c\/p\u003e \u003cp\u003e6.5.1 Skew Symmetry and Passivity 194\u003c\/p\u003e \u003cp\u003e6.5.2 Bounds on the Inertia Matrix 196\u003c\/p\u003e \u003cp\u003e6.5.3 Linearity in the Parameters 196\u003c\/p\u003e \u003cp\u003e6.6 Newton-Euler Formulation 198\u003c\/p\u003e \u003cp\u003e6.6.1 Planar Elbow Manipulator Revisited 206\u003c\/p\u003e \u003cp\u003e6.7 Chapter Summary 209\u003c\/p\u003e \u003cp\u003eProblems 211\u003c\/p\u003e \u003cp\u003eNotes and References 214\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Path and Trajectory Planning 215\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 The Configuration Space 216\u003c\/p\u003e \u003cp\u003e7.1.1 Representing the Configuration Space 217\u003c\/p\u003e \u003cp\u003e7.1.2 Configuration Space Obstacles 218\u003c\/p\u003e \u003cp\u003e7.1.3 Paths in the Configuration Space 221\u003c\/p\u003e \u003cp\u003e7.2 Path Planning for Q = ℝ\u003csup\u003e2\u003c\/sup\u003e 221\u003c\/p\u003e \u003cp\u003e7.2.1 The Visibility Graph 222\u003c\/p\u003e \u003cp\u003e7.2.2 The Generalized Voronoi Diagram 224\u003c\/p\u003e \u003cp\u003e7.2.3 Trapezoidal Decompositions 226\u003c\/p\u003e \u003cp\u003e7.3 Artificial Potential Fields 229\u003c\/p\u003e \u003cp\u003e7.3.1 Artificial Potential Fields for Q = ℝ\u003ci\u003e\u003csup\u003en\u003c\/sup\u003e \u003c\/i\u003e230\u003c\/p\u003e \u003cp\u003e7.3.2 Potential Fields for Q ≠ ℝ\u003ci\u003e\u003csup\u003en\u003c\/sup\u003e \u003c\/i\u003e235\u003c\/p\u003e \u003cp\u003e7.4 Sampling-Based Methods 245\u003c\/p\u003e \u003cp\u003e7.4.1 Probabilistic Roadmaps (PRM) 246\u003c\/p\u003e \u003cp\u003e7.4.2 Rapidly-Exploring Random Trees (RRTs) 250\u003c\/p\u003e \u003cp\u003e7.5 Trajectory Planning 252\u003c\/p\u003e \u003cp\u003e7.5.1 Trajectories for Point-to-Point Motion 253\u003c\/p\u003e \u003cp\u003e7.5.2 Trajectories for Paths Specified by Via Points 261\u003c\/p\u003e \u003cp\u003e7.6 Chapter Summary 263\u003c\/p\u003e \u003cp\u003eProblems 265\u003c\/p\u003e \u003cp\u003eNotes and References 267\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIII Control of Manipulators 269\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Independent Joint Control 271\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 271\u003c\/p\u003e \u003cp\u003e8.2 Actuator Dynamics 273\u003c\/p\u003e \u003cp\u003e8.3 Load Dynamics 276\u003c\/p\u003e \u003cp\u003e8.4 Independent Joint Model 278\u003c\/p\u003e \u003cp\u003e8.5 PID Control 281\u003c\/p\u003e \u003cp\u003e8.6 Feedforward Control 288\u003c\/p\u003e \u003cp\u003e8.6.1 Trajectory Tracking 289\u003c\/p\u003e \u003cp\u003e8.6.2 The Method of Computed Torque 291\u003c\/p\u003e \u003cp\u003e8.7 Drive-Train Dynamics 292\u003c\/p\u003e \u003cp\u003e8.8 State Space Design 297\u003c\/p\u003e \u003cp\u003e8.8.1 State Feedback Control 299\u003c\/p\u003e \u003cp\u003e8.8.2 Observers 301\u003c\/p\u003e \u003cp\u003e8.9 Chapter Summary 304\u003c\/p\u003e \u003cp\u003eProblems 307\u003c\/p\u003e \u003cp\u003eNotes and References 309\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Nonlinear and Multivariable Control 311\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 311\u003c\/p\u003e \u003cp\u003e9.2 PD Control Revisited 313\u003c\/p\u003e \u003cp\u003e9.3 Inverse Dynamics 317\u003c\/p\u003e \u003cp\u003e9.3.1 Joint Space Inverse Dynamics 317\u003c\/p\u003e \u003cp\u003e9.3.2 Task Space Inverse Dynamics 320\u003c\/p\u003e \u003cp\u003e9.3.3 Robust Inverse Dynamics 322\u003c\/p\u003e \u003cp\u003e9.3.4 Adaptive Inverse Dynamics 327\u003c\/p\u003e \u003cp\u003e9.4 Passivity-Based Control 329\u003c\/p\u003e \u003cp\u003e9.4.1 Passivity-Based Robust Control 331\u003c\/p\u003e \u003cp\u003e9.4.2 Passivity-Based Adaptive Control 332\u003c\/p\u003e \u003cp\u003e9.5 Torque Optimization 333\u003c\/p\u003e \u003cp\u003e9.6 Chapter Summary 337\u003c\/p\u003e \u003cp\u003eProblems 341\u003c\/p\u003e \u003cp\u003eNotes and References 343\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Force Control 345\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Coordinate Frames and Constraints 347\u003c\/p\u003e \u003cp\u003e10.1.1 Reciprocal Bases 347\u003c\/p\u003e \u003cp\u003e10.1.2 Natural and Artificial Constraints 349\u003c\/p\u003e \u003cp\u003e10.2 Network Models and Impedance 351\u003c\/p\u003e \u003cp\u003e10.2.1 Impedance Operators 353\u003c\/p\u003e \u003cp\u003e10.2.2 Classification of Impedance Operators 354\u003c\/p\u003e \u003cp\u003e10.2.3 Thévenin and Norton Equivalents 355\u003c\/p\u003e \u003cp\u003e10.3 Task Space Dynamics and Control 355\u003c\/p\u003e \u003cp\u003e10.3.1 Impedance Control 356\u003c\/p\u003e \u003cp\u003e10.3.2 Hybrid Impedance Control 358\u003c\/p\u003e \u003cp\u003e10.4 Chapter Summary 361\u003c\/p\u003e \u003cp\u003eProblems 362\u003c\/p\u003e \u003cp\u003eNotes and References 364\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Vision-Based Control 365\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Design Considerations 366\u003c\/p\u003e \u003cp\u003e11.1.1 Camera Configuration 366\u003c\/p\u003e \u003cp\u003e11.1.2 Image-Based vs. Position-Based Approaches 367\u003c\/p\u003e \u003cp\u003e11.2 Computer Vision for Vision-Based Control 368\u003c\/p\u003e \u003cp\u003e11.2.1 The Geometry of Image Formation 369\u003c\/p\u003e \u003cp\u003e11.2.2 Image Features 373\u003c\/p\u003e \u003cp\u003e11.3 Camera Motion and the Interaction Matrix 378\u003c\/p\u003e \u003cp\u003e11.4 The Interaction Matrix for Point Features 379\u003c\/p\u003e \u003cp\u003e11.4.1 Velocity Relative to a Moving Frame 380\u003c\/p\u003e \u003cp\u003e11.4.2 Constructing the Interaction Matrix 381\u003c\/p\u003e \u003cp\u003e11.4.3 Properties of the Interaction Matrix for Points 384\u003c\/p\u003e \u003cp\u003e11.4.4 The Interaction Matrix for Multiple Points 385\u003c\/p\u003e \u003cp\u003e11.5 Image-Based Control Laws 386\u003c\/p\u003e \u003cp\u003e11.5.1 Computing Camera Motion 387\u003c\/p\u003e \u003cp\u003e11.5.2 Proportional Control Schemes 389\u003c\/p\u003e \u003cp\u003e11.5.3 Performance of Image-Based Control Systems 390\u003c\/p\u003e \u003cp\u003e11.6 End Effector and Camera Motions 393\u003c\/p\u003e \u003cp\u003e11.7 Partitioned Approaches 394\u003c\/p\u003e \u003cp\u003e11.8 Motion Perceptibility 397\u003c\/p\u003e \u003cp\u003e11.9 Summary 399\u003c\/p\u003e \u003cp\u003eProblems 401\u003c\/p\u003e \u003cp\u003eNotes and References 405\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Feedback Linearization 409\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Background 410\u003c\/p\u003e \u003cp\u003e12.1.1 Manifolds, Vector Fields, and Distributions 410\u003c\/p\u003e \u003cp\u003e12.1.2 The Frobenius Theorem 414\u003c\/p\u003e \u003cp\u003e12.2 Feedback Linearization 417\u003c\/p\u003e \u003cp\u003e12.3 Single-Input Systems 419\u003c\/p\u003e \u003cp\u003e12.4 Multi-Input Systems 429\u003c\/p\u003e \u003cp\u003e12.5 Chapter Summary 433\u003c\/p\u003e \u003cp\u003eProblems 433\u003c\/p\u003e \u003cp\u003eNotes and References 435\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIV Control of Underactuated Systems 437\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Underactuated Robots 439\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 439\u003c\/p\u003e \u003cp\u003e13.2 Modeling 440\u003c\/p\u003e \u003cp\u003e13.3 Examples of Underactuated Robots 443\u003c\/p\u003e \u003cp\u003e13.3.1 The Cart-Pole System 443\u003c\/p\u003e \u003cp\u003e13.3.2 The Acrobot 445\u003c\/p\u003e \u003cp\u003e13.3.3 The Pendubot 446\u003c\/p\u003e \u003cp\u003e13.3.4 The Reaction-Wheel Pendulum 447\u003c\/p\u003e \u003cp\u003e13.4 Equilibria and Linear Controllability 448\u003c\/p\u003e \u003cp\u003e13.4.1 Linear Controllability 450\u003c\/p\u003e \u003cp\u003e13.5 Partial Feedback Linearization 456\u003c\/p\u003e \u003cp\u003e13.5.1 Collocated Partial Feedback Linearization 457\u003c\/p\u003e \u003cp\u003e13.5.2 Noncollocated Partial Feedback Linearization 459\u003c\/p\u003e \u003cp\u003e13.6 Output Feedback Linearization 461\u003c\/p\u003e \u003cp\u003e13.6.1 Computation of the Zero Dynamics 463\u003c\/p\u003e \u003cp\u003e13.6.2 Virtual Holonomic Constraints 466\u003c\/p\u003e \u003cp\u003e13.7 Passivity-Based Control 466\u003c\/p\u003e \u003cp\u003e13.7.1 The Simple Pendulum 467\u003c\/p\u003e \u003cp\u003e13.7.2 The Reaction-Wheel Pendulum 471\u003c\/p\u003e \u003cp\u003e13.7.3 Swingup and Balance of The Acrobot 473\u003c\/p\u003e \u003cp\u003e13.8 Chapter Summary 474\u003c\/p\u003e \u003cp\u003eProblems 476\u003c\/p\u003e \u003cp\u003eNotes and References 477\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Mobile Robots 479\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Nonholonomic Constraints 480\u003c\/p\u003e \u003cp\u003e14.2 Involutivity and Holonomy 484\u003c\/p\u003e \u003cp\u003e14.3 Examples of Nonholonomic Systems 487\u003c\/p\u003e \u003cp\u003e14.4 Dynamic Extension 493\u003c\/p\u003e \u003cp\u003e14.5 Controllability of Driftless Systems 495\u003c\/p\u003e \u003cp\u003e14.6 Motion Planning 499\u003c\/p\u003e \u003cp\u003e14.6.1 Conversion to Chained Forms 499\u003c\/p\u003e \u003cp\u003e14.6.2 Differential Flatness 506\u003c\/p\u003e \u003cp\u003e14.7 Feedback Control of Driftless Systems 509\u003c\/p\u003e \u003cp\u003e14.7.1 Stabilizability 509\u003c\/p\u003e \u003cp\u003e14.7.2 Nonsmooth Control 511\u003c\/p\u003e \u003cp\u003e14.7.3 Trajectory Tracking 513\u003c\/p\u003e \u003cp\u003e14.7.4 Feedback Linearization 515\u003c\/p\u003e \u003cp\u003e14.8 Chapter Summary 519\u003c\/p\u003e \u003cp\u003eProblems 520\u003c\/p\u003e \u003cp\u003eNotes and References 521\u003c\/p\u003e \u003cp\u003e\u003cb\u003eA Trigonometry 523\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 The Two-Argument Arctangent Function 523\u003c\/p\u003e \u003cp\u003eA.2 Useful Trigonometric Formulas 523\u003c\/p\u003e \u003cp\u003e\u003cb\u003eB Linear Algebra 525\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eB.1 Vectors 525\u003c\/p\u003e \u003cp\u003eB.2 Inner Product Spaces 526\u003c\/p\u003e \u003cp\u003eB.3 Matrices 528\u003c\/p\u003e \u003cp\u003eB.4 Eigenvalues and Eigenvectors 530\u003c\/p\u003e \u003cp\u003eB.5 Differentiation of Vectors 533\u003c\/p\u003e \u003cp\u003eB.6 The Matrix Exponential 534\u003c\/p\u003e \u003cp\u003eB.7 Lie Groups and Lie Algebras 534\u003c\/p\u003e \u003cp\u003eB.8 Matrix Pseudoinverse 536\u003c\/p\u003e \u003cp\u003eB.9 Schur Complement 536\u003c\/p\u003e \u003cp\u003eB.10 Singular Value Decomposition (SVD) 537\u003c\/p\u003e \u003cp\u003e\u003cb\u003eC Lyapunov Stability 539\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eC.1 Continuity and Differentiability 539\u003c\/p\u003e \u003cp\u003eC.2 Vector Fields and Equilibria 541\u003c\/p\u003e \u003cp\u003eC.3 Lyapunov Functions 545\u003c\/p\u003e \u003cp\u003eC.4 Stability Criteria 545\u003c\/p\u003e \u003cp\u003eC.5 Global and Exponential Stability 546\u003c\/p\u003e \u003cp\u003eC.6 Stability of Linear Systems 547\u003c\/p\u003e \u003cp\u003eC.7 LaSalle's Theorem 548\u003c\/p\u003e \u003cp\u003eC.8 Barbalat's Lemma 549\u003c\/p\u003e \u003cp\u003e\u003cb\u003eD Optimization 551\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eD.1 Unconstrained Optimization 551\u003c\/p\u003e \u003cp\u003eD.2 Constrained Optimization 552\u003c\/p\u003e \u003cp\u003e\u003cb\u003eE Camera Calibration 555\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eE.1 The Image Plane and the Sensor Array 555\u003c\/p\u003e \u003cp\u003eE.2 Extrinsic Camera Parameters 556\u003c\/p\u003e \u003cp\u003eE.3 Intrinsic Camera Parameters 557\u003c\/p\u003e \u003cp\u003eE.4 Determining the Camera Parameters 557\u003c\/p\u003e \u003cp\u003eBibliography 561\u003c\/p\u003e \u003cp\u003eIndex 576\u003c\/p\u003e   \u003cp\u003e\u003cb\u003eMARK W. SPONG\u003c\/b\u003e has been researching and teaching robotics for over 35 years. He currently serves as a Professor, Excellence in Education Chair, in the Department of Systems Engineering at the University of Texas at Dallas. He has been recognized for outstanding achievements including the John R. Ragazzini Award for Control Education and the IEEE RAS Pioneer in Robotics Award. He is currently a Fellow of both IEEE and IFAC. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eSETH HUTCHINSON\u003c\/b\u003e received his Ph.D. from Purdue University in 1988, and is currently Professor and KUKA Chair for Robotics in the School of Interactive Computing at the Georgia Institute of Technology, where he also serves as Executive Director of the Institute for Robotics and Intelligent Machines. He was the Founding Editor-in-Chief of the IEEE Robotics and Automation Society's Conference Editorial Board, Editor-in-Chief of the IEEE Transactions on Robotics, and is a Fellow of the IEEE. His research in robotics spans the areas of planning, sensing, and control. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eMATHUKUMALLI VIDYASAGAR\u003c\/b\u003e received his Ph.D. in electrical engineering in 1969 from the University of Wisconsin in Madison. During his fifty-year career, he has worked in control theory, machine learning, robotics and cancer biology. Among the many honors he has received are Fellowship in The Royal Society and the IEEE Control Systems Award. At present he is a Distinguished Professor at the Indian Institute of Technology Hyderabad.    \u003c\/p\u003e\u003cp\u003e\u003cb\u003eA NEW EDITION FEATURING CASE STUDIES AND EXAMPLES OF THE FUNDAMENTALS OF ROBOT KINEMATICS, DYNAMICS, AND CONTROL\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eIn the Second Edition of \u003ci\u003eRobot Modeling and Control\u003c\/i\u003e, students will cover the theoretical fundamentals and the latest technological advances in robot kinematics. With so much advancement in technology, from robotics to motion planning, society can implement more powerful and dynamic algorithms than ever before. This in-depth reference guide educates readers in four distinct parts; the first two serve as a guide to the fundamentals of robotics and motion control, while the last two dive more in-depth into control theory and nonlinear system analysis. \u003c\/p\u003e\u003cp\u003eWith the new edition, readers gain access to new case studies and thoroughly researched information covering topics such as: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eMotion-planning, collision avoidance, trajectory optimization, and control of robots\u003c\/li\u003e \u003cli\u003ePopular topics within the robotics industry and how they apply to various technologies\u003c\/li\u003e \u003cli\u003eAn expanded set of examples, simulations, problems, and case studies\u003c\/li\u003e \u003cli\u003eOpen-ended suggestions for students to apply the knowledge to real-life situations\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eA four-part reference essential for both undergraduate and graduate students, \u003ci\u003eRobot Modeling and Control\u003c\/i\u003e serves as a foundation for a solid education in robotics and motion planning.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989969944805,"sku":"NP9781119523994","price":121.5,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119523994.jpg?v=1761786072","url":"https:\/\/k12savings.com\/products\/robot-modeling-and-control-isbn-9781119523994","provider":"K12savings","version":"1.0","type":"link"}