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by Kwok-wai Au. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 55-58). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.iii / Contents --- p.iv / List of Figures --- p.vi / List of Tables --- p.viii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Previous work --- p.5 / Chapter 1.3 --- Thesis overview --- p.7 / Chapter 2 --- Dynamics of the Single Wheel Robot --- p.10 / Chapter 2.1 --- Dynamic model of a rolling disk --- p.10 / Chapter 2.1.1 --- Kinematic constraints --- p.11 / Chapter 2.1.2 --- Equations of motion --- p.13 / Chapter 2.1.3 --- Characteristics of the rolling disk --- p.15 / Chapter 2.2 --- Dynamic model of the single wheel robot --- p.18 / Chapter 2.2.1 --- Coordinate frames and generalized coordinates --- p.19 / Chapter 2.2.2 --- Equations of motion --- p.21 / Chapter 2.2.3 --- Model simplification --- p.24 / Chapter 2.3 --- Dynamic properties of the single wheel robot --- p.27 / Chapter 3 --- Stabilization of the Single Wheel Robot --- p.30 / Chapter 3.1 --- Linearized model --- p.30 / Chapter 3.2 --- Controllability and non-minimum phase characteristics --- p.33 / Chapter 3.3 --- Linear state feedback --- p.33 / Chapter 3.4 --- Simulation Study --- p.35 / Chapter 4 --- Path Following of the Single Wheel Robot --- p.37 / Chapter 4.1 --- Path following for nonholonomic systems --- p.37 / Chapter 4.2 --- Definition of path following --- p.39 / Chapter 4.3 --- New configuration --- p.39 / Chapter 4.4 --- Line following --- p.41 / Chapter 4.4.1 --- Velocity control law --- p.42 / Chapter 4.4.2 --- Convergence for the velocity control law --- p.43 / Chapter 4.4.3 --- Torque control law --- p.45 / Chapter 4.5 --- Simulation study --- p.47 / Chapter 4.5.1 --- Effect of the initial heading angle --- p.47 / Chapter 4.5.2 --- Effect of the rolling speed --- p.49 / Chapter 4.5.3 --- Follow a desired line --- p.50 / Chapter 4.5.4 --- Effect of the smoothness parameter --- p.50 / Chapter 5 --- Conclusion --- p.52 / Chapter 5.1 --- Contributions --- p.52 / Chapter 5.2 --- Future work --- p.53 / Bibliography --- p.55

by Wai-Kuen Yu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 83-87). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Robot Concept --- p.1 / Chapter 1.2 --- Motivations --- p.3 / Chapter 1.3 --- Related Work --- p.5 / Chapter 1.4 --- Overview --- p.6 / Chapter 2 --- Single Wheel Robot --- p.8 / Chapter 2.1 --- Mathematical Model --- p.8 / Chapter 2.1.1 --- Coordinate Frame --- p.9 / Chapter 2.1.2 --- Equations of Motion --- p.10 / Chapter 2.1.3 --- Model Simplification --- p.12 / Chapter 2.2 --- Hardware Descriptions --- p.13 / Chapter 2.2.1 --- Actuators --- p.14 / Chapter 2.2.2 --- Sensors --- p.14 / Chapter 2.2.3 --- Communication Subsystem --- p.15 / Chapter 2.2.4 --- Computer Subsystem --- p.16 / Chapter 2.3 --- Software Descriptions --- p.16 / Chapter 2.3.1 --- Operating System --- p.17 / Chapter 2.3.2 --- Software Architecture --- p.18 / Chapter 3 --- Human-based Control --- p.21 / Chapter 3.1 --- Why Human-based Control --- p.21 / Chapter 3.2 --- Modeling Human Control Strategy --- p.22 / Chapter 3.2.1 --- Human Control Strategy --- p.22 / Chapter 3.2.2 --- Neural Network for Modeling --- p.23 / Chapter 3.2.3 --- Learning Procedure --- p.24 / Chapter 3.3 --- Task Descriptions --- p.28 / Chapter 3.4 --- Modeling HCS in Controlling the Robot --- p.29 / Chapter 3.4.1 --- Model Input and Output --- p.30 / Chapter 3.4.2 --- Human-based Controller --- p.31 / Chapter 3.5 --- Result and Discussion --- p.31 / Chapter 4 --- Input Selection --- p.38 / Chapter 4.1 --- Why Input Selection --- p.38 / Chapter 4.2 --- Model Validation --- p.39 / Chapter 4.2.1 --- Why Model Validation --- p.39 / Chapter 4.2.2 --- Root Mean Square Error Measure --- p.40 / Chapter 4.3 --- Experimental Setup --- p.40 / Chapter 4.4 --- Model-based Method --- p.41 / Chapter 4.4.1 --- Problem Definition --- p.41 / Chapter 4.4.2 --- Input Representation --- p.43 / Chapter 4.4.3 --- Sensitivity Analysis --- p.44 / Chapter 4.4.4 --- Experimental Result --- p.47 / Chapter 4.5 --- Model-free Method --- p.51 / Chapter 4.5.1 --- Problems Definition --- p.51 / Chapter 4.5.2 --- Factor Analysis --- p.54 / Chapter 4.5.3 --- Experimental Result --- p.63 / Chapter 4.6 --- Model-based Method versus Model-free Method --- p.66 / Chapter 5 --- Conclusion and Future Work --- p.71 / Chapter 5.1 --- Contributions --- p.71 / Chapter 5.2 --- Future Work --- p.72 / Chapter Appendix A --- Dynamic Model of the Robot --- p.74 / Chapter A.1 --- Kinematic Constraints: Holonomic and Nonholonomic --- p.74 / Chapter A.1.1 --- Coordinate Frame --- p.74 / Chapter A.2 --- Robot Dynamics --- p.76 / Chapter A.2.1 --- Single Wheel --- p.77 / Chapter A.2.2 --- Internal Mechanism and Spinning Flywheel --- p.77 / Chapter A.2.3 --- Lagrangians of the System --- p.78 / Chapter Appendix B --- Similarity Measure --- p.80 / Bibliography --- p.82

by Loi-Wah Sun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 77-81). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.iii / Contents --- p.v / List of Figures --- p.vii / List of Tables --- p.viii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.1.1 --- Literature review --- p.2 / Chapter 1.1.2 --- Gyroscopic precession --- p.5 / Chapter 1.2 --- Thesis overview --- p.7 / Chapter 2 --- Dynamics of the robot on ground --- p.9 / Chapter 2.1 --- System model re-derivation --- p.10 / Chapter 2.1.1 --- Linearized model --- p.15 / Chapter 2.2 --- A state feedback control --- p.16 / Chapter 2.3 --- Dynamic characteristics of the system --- p.18 / Chapter 2.4 --- Simulation study --- p.19 / Chapter 2.4.1 --- The self-stabilizing dynamics effect of the single wheel robot --- p.21 / Chapter 2.4.2 --- The Tilting effect of flywheel on the robot --- p.23 / Chapter 2.5 --- Dynamic parameters analysis --- p.25 / Chapter 2.5.1 --- Swinging pendulum --- p.25 / Chapter 2.5.2 --- Analysis of radius ratios --- p.27 / Chapter 2.5.3 --- Analysis of mass ratios --- p.30 / Chapter 3 --- Dynamics of the robot on incline --- p.33 / Chapter 3.1 --- Modeling of rolling disk on incline --- p.33 / Chapter 3.1.1 --- Disk rolls up on an inclined plane --- p.37 / Chapter 3.2 --- Modeling of single wheel robot on incline --- p.39 / Chapter 3.2.1 --- Kinematic constraints --- p.40 / Chapter 3.2.2 --- Equations of motion --- p.41 / Chapter 3.2.3 --- Model simplification --- p.43 / Chapter 3.2.4 --- Linearized model --- p.46 / Chapter 4 --- Control of the robot on incline --- p.47 / Chapter 4.1 --- A state feedback control --- p.47 / Chapter 4.1.1 --- Simulation study --- p.49 / Chapter 4.2 --- Backstepping-based control --- p.51 / Chapter 4.2.1 --- Simulation study --- p.53 / Chapter 4.2.2 --- The effect of the spinning rate of flywheel --- p.56 / Chapter 4.2.3 --- Simulation study --- p.58 / Chapter 4.2.4 --- Roll up case --- p.58 / Chapter 4.2.5 --- Roll down case --- p.58 / Chapter 5 --- Motion planning --- p.61 / Chapter 5.1 --- Performance index --- p.61 / Chapter 5.2 --- Condition of rolling up --- p.62 / Chapter 5.3 --- Motion planning of rolling Up --- p.65 / Chapter 5.3.1 --- Method I : Orientation change --- p.65 / Chapter 5.3.2 --- Method II : Change the initial velocities --- p.69 / Chapter 5.4 --- Wheel rolls Down --- p.70 / Chapter 5.4.1 --- Terminal velocity of rolling body down --- p.73 / Chapter 6 --- Summary --- p.75 / Chapter 6.1 --- Contributions --- p.75 / Chapter 6.2 --- Future Works --- p.76 / Bibliography --- p.78

After capturing the object, the space robot must complete the following two tasks: one is to berth the object, and the other is to re-orientate the attitude of the whole robot system for communication and power supply. Therefore, I propose a method to accomplish these two tasks simultaneously using manipulator motion only. / Finally I propose a novel approach based on Genetic Algorithms (GAs) to optimize the approach trajectory of space robots in order to realize effective and stable operations. I complete the minimum-torque path planning in order to save the limited energy in space, and design the minimum jerk trajectory for the stabilization of the space manipulator and its space base. These optimal algorithms are very important and useful for the application of space robot. / In this thesis, I study and analyze the dynamics and control problems of space robot for capturing objects. This work has potential impact in space robotic applications. I first study the contact and impact dynamics of space robot and objects. I specifically focus on analyzing the impact dynamics and mapping the relationship of influence and speed. Then, I develop the fundamental theory for planning the minimum-collision based trajectory of space robot and designing the configuration of space robot at the moment of capture. / Space robots are expected to perform intricate tasks in future space services, such as satellite maintenance, refueling, and replacing the orbital replacement unit (ORU). To realize these missions, the capturing operation may not be avoided. Such operations will encounter some challenges because space robots have some unique characteristics unfound on ground-based robots, such as, dynamic singularities, dynamic coupling between manipulator and space base, limited energy supply and working without a fixed base, and so on. In addition, since contacts and impacts may not be avoided during capturing operation. Therefore, dynamics and control problems of space robot for capturing objects are significant research topics if the robots are to be deployed for the space services. A typical servicing operation mainly includes three phases: capturing the object, berthing and docking the object, then repairing the target. Therefore, this thesis will focus on resolving some challenging problems during capturing the object, berthing and docking, and so on. / The ultimate goal of space services is to realize the capture and manipulation autonomously. Therefore, I propose an affective approach based on learning human skill to track and capture the objects automatically in space. With human-teaching demonstration, the space robot is able to learn and abstract human tracking and capturing skill using an efficient neural-network learning architecture that combines flexible Cascade Neural Networks with Node Decoupled Extended Kalman Filtering (CNN-NDEKF). The simulation results attest that this approach is useful and feasible in tracking trajectory planning and capturing of space robot. / To compensate for the attitude of the space base during the capturing approach operation, a new balance control concept which can effectively balance the attitude of the space base using the dynamic couplings is developed. The developed balance control concept helps to understand of the nature of space dynamic coupling, and can be readily applied to compensate or minimize the disturbance to the space base. / Huang Panfeng. / "December 2005." / Adviser: Yang Sheng Xu. / Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6693. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (p. 133-143). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

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The development of modern industries calls for the robotic manipulators with high speed and accurate tracking performance. Many authors have paid attention to robust control of robotic manipulators; however, only few authors have also considered the control problem of manipulators with power limitation. In this dissertation, the robotic manipulator is modeled as an uncertain system, with such uncertainties as varying moments of inertia, damping and payloads during tracking. The resulting uncertain part of the system is norm-bounded by a known constant. The total control consists of a linear part with gain matrix K, and a nonlinear part Δv, typically used for control of uncertain dynamical systems. Saturation of the resulting controller is assumed, with bounds imposed by the power limitation of actuators. It is proved at the dissertation that such a system is globally uniformly practically stable. The distribution of the control power between two controllers is discussed. It is found that when small gain matrix K is used and Δv dominates the controller, the solution to the system can approach a smaller region with faster response; that is, higher tracking accuracy is obtained. Theoretical analysis is provided to support the proposed control scheme. A two-link robotic manipulator is simulated with the results confirming the prediction. / Graduation date: 1992

Cartesian space path planning involves generating the position and orientation trajectories for a manipulator end-effector. Currently, much of the literature in motion planning for robotics concentrates on topics such as obstacle avoidance, dynamic optimizations, or high-level task planning. The focus of this research is on operator-generated motions. This will involve analytically studying the effects of higher-order properties (such as curvature and torsion) on the shape of spatial Cartesian curves. A particular emphasis will be placed on developing physical meanings and graphical visualization for these properties to aid the operator in generating geometrically complex motions. This research begins with a brief introduction to the domain of robotics and manipulator motion planning. An overview of work in the area of manipulator motion planning will demonstrate a lack of research on generating geometrically complex spatial paths. To pursue this goal, this report will then provide a review of the theory of algrebraic curves and their higher-order properties. This involves an evaluation of several different representations for both planar and spatial curves. Then, a survey of interactive curve generation techniques will be performed, which will draw from fields outside of robotics such as Computer Graphics and Computer-Aided Design (CAD). In addition to the reviewed methods, a new method for describing and generating spatial curves is proposed and demonstrated. This method begins with the study of a finite set of local geometric motion shapes (circular arcs, cusps, helices, etc). The local geometric shapes are studied in terms of their geometric parameters (curvature and torsion), analyzed to give physical meaning to these parameters, and displayed graphically as a family of curves based on these controlling parameters. This leads to the development of path constraints with well-defined physical meaning. Then, a curve generation method is developed that can convert these geometric constraints into parametric constraints and blend between them to form a complete motion program (cycle) of smooth paths connecting several carefully developed local curve properties. Up to ten distinct local curve shapes were developed in detail and one curve cycle demonstrated how all this could be combined into a full path planning scenario. Finally, the developed methods are packaged together into existing software and applied to an example demonstration. / text

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