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Recurrent neural networks for inverse kinematics and inverse dynamics computation of redundant manipulators.January 1999 (has links)
Tang Wai Sum. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 68-70). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Redundant Manipulators --- p.1 / Chapter 1.2 --- Inverse Kinematics of Robotic Manipulators --- p.2 / Chapter 1.3 --- Inverse Dynamics of Robotic Manipulators --- p.4 / Chapter 1.4 --- Redundancy Resolutions of Manipulators --- p.5 / Chapter 1.5 --- Motivation of Using Neural Networks for these Applications --- p.9 / Chapter 1.6 --- Previous Work for Redundant Manipulator Inverse Kinematics and Inverse Dynamics Computation by Neural Networks --- p.9 / Chapter 1.7 --- Advantages of the Proposed Recurrent Neural Networks --- p.11 / Chapter 1.8 --- Contribution of this work --- p.11 / Chapter 1.9 --- Organization of this thesis --- p.12 / Chapter 2 --- Problem Formulations --- p.14 / Chapter 2.1 --- Constrained Optimization Problems for Inverse Kinematics Com- putation of Redundant Manipulators --- p.14 / Chapter 2.1.1 --- Primal and Dual Quadratic Programs for Bounded Joint Velocity Minimization --- p.14 / Chapter 2.1.2 --- Primal and Dual Linear Programs for Infinity-norm Joint Velocity Minimization --- p.15 / Chapter 2.2 --- Constrained Optimization Problems for Inverse Dynamics Com- putation of Redundant Manipulators --- p.17 / Chapter 2.2.1 --- Quadratic Program for Unbounded Joint Torque Mini- mization --- p.17 / Chapter 2.2.2 --- Primal and Dual Quadratic Programs for Bounded Joint Torque Minimization --- p.18 / Chapter 2.2.3 --- Primal and Dual Linear Programs for Infinity-norm Joint Torque Minimization --- p.19 / Chapter 3 --- Proposed Recurrent Neural Networks --- p.20 / Chapter 3.1 --- The Lagrangian Network --- p.21 / Chapter 3.1.1 --- Optimality Conditions for Unbounded Joint Torque Min- imization --- p.21 / Chapter 3.1.2 --- Dynamical Equations and Architecture --- p.22 / Chapter 3.2 --- The Primal-Dual Network 1 --- p.24 / Chapter 3.2.1 --- Optimality Conditions for Bounded Joint Velocity Min- imization --- p.24 / Chapter 3.2.2 --- Dynamical Equations and Architecture for Bounded Joint Velocity Minimization --- p.26 / Chapter 3.2.3 --- Optimality Conditions for Bounded Joint Torque Mini- mization --- p.27 / Chapter 3.2.4 --- Dynamical Equations and Architecture for Bounded Joint Torque Minimization --- p.28 / Chapter 3.3 --- The Primal-Dual Network 2 --- p.29 / Chapter 3.3.1 --- Energy Function for Infinity-norm Joint Velocity Mini- mization Problem --- p.29 / Chapter 3.3.2 --- Dynamical Equations for Infinity-norm Joint Velocity Minimization --- p.30 / Chapter 3.3.3 --- Energy Functions for Infinity-norm Joint Torque Mini- mization Problem --- p.32 / Chapter 3.3.4 --- Dynamical Equations for Infinity-norm Joint Torque Min- imization --- p.32 / Chapter 3.4 --- Selection of the Positive Scaling Constant --- p.33 / Chapter 4 --- Stability Analysis of Neural Networks --- p.36 / Chapter 4.1 --- The Lagrangian Network --- p.36 / Chapter 4.2 --- The Primal-Dual Network 1 --- p.38 / Chapter 4.3 --- The Primal-Dual Network 2 --- p.41 / Chapter 5 --- Simulation Results and Network Complexity --- p.45 / Chapter 5.1 --- Simulation Results of Inverse Kinematics Computation in Re- dundant Manipulators --- p.45 / Chapter 5.1.1 --- Bounded Least Squares Joint Velocities Computation Using the Primal-Dual Network 1 --- p.46 / Chapter 5.1.2 --- Minimum Infinity-norm Joint Velocities Computation Us- ing the Primal-Dual Network 2 --- p.49 / Chapter 5.2 --- Simulation Results of Inverse Dynamics Computation in Redun- dant Manipulators --- p.51 / Chapter 5.2.1 --- Minimum Unbounded Joint Torques Computation Using the Lagrangian Network --- p.54 / Chapter 5.2.2 --- Minimum Bounded Joint Torques Computation Using the Primal-Dual Network 1 --- p.57 / Chapter 5.2.3 --- Minimum Infinity-norm Joint Torques Computation Us- ing the Primal-Dual Network 2 --- p.59 / Chapter 5.3 --- Network Complexity Analysis --- p.60 / Chapter 6 --- Concluding Remarks and Future Work --- p.64 / Publications Resulted from the Study --- p.66 / Bibliography --- p.68
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