Orientador: Edson de Paula Ferreira / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica / Made available in DSpace on 2018-07-13T23:45:43Z (GMT). No. of bitstreams: 1 Silva_JorgeVicenteLopesda_M.pdf: 6182719 bytes, checksum: e4b7bfe60d4781e5ea10c6ce2172417d (MD5) Previous issue date: 1990 / Resumo: Este trabalho apresenta contribuições no sentido de agilizar e otimizar a modelagem geométrica e dinâmica de robôs. A finalidade principal na utilização destes modelos é o desenvolvimento de estratégias de controle mais eficientes, que consigam compensar efeitos indesejáveis, quando é exigido um desempenho superior dos robôs. Estes modelos são de grande complexidade e sua obtenção manual, além de demorada, é extremamente árida e bastante sujeita a erros. Por este motivo, implementamos um sistema para a geração automática de modelos geométricos e modelos dinâmicos com base no formalismo de Lagrange, utilizando recursos para otimização destes modelos. É proposto um algoritmo eficiente para modelagem dinâmica, o qual elimina automaticamente um grande número de redundâncias. Este algoritmo é apresentado à nível de implementação / Abstract: This work presents contributions aiming at time saving and model improvement in the generation of geometric and dynamic robot models. The main purpose is to enable the generation of models suited for use in the development of more efficient control strategies, 50 as to compensa te effects that become undesirable when a better robot performance is required. These are quite complex models and the manual derivation of them is tedious, costly (time-consuming) and often error-prone. 50, it was implemented a system for automatic generation of symbolic geometric and dynamic robot models based in the Lagrange formulation and that also cares about model optimization. It is also proposed an efficient algorithm for dynamic modelling, which automatically eliminates a great number of redundancies. This algorithm is presented in the implementation level / Mestrado / Automação / Mestre em Engenharia Elétrica

by Law Kwok Ho Cedric. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 106-112). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Related work --- p.4 / Chapter 1.3 --- Thesis overview --- p.5 / Chapter 2 --- Single wheel robot: Gyrover --- p.9 / Chapter 2.1 --- Background --- p.9 / Chapter 2.2 --- Robot concept --- p.11 / Chapter 2.3 --- System description --- p.14 / Chapter 2.4 --- Flywheel characteristics --- p.16 / Chapter 2.5 --- Control patterns --- p.20 / Chapter 3 --- Learning Control --- p.22 / Chapter 3.1 --- Motivation --- p.22 / Chapter 3.2 --- Cascade Neural Network with Kalman filtering --- p.24 / Chapter 3.3 --- Learning architecture --- p.27 / Chapter 3.4 --- Input space --- p.29 / Chapter 3.5 --- Model evaluation --- p.30 / Chapter 3.6 --- Training procedures --- p.35 / Chapter 4 --- Control Architecture --- p.38 / Chapter 4.1 --- Behavior-based approach --- p.38 / Chapter 4.1.1 --- Concept and applications --- p.39 / Chapter 4.1.2 --- Levels of competence --- p.44 / Chapter 4.2 --- Behavior-based control of Gyrover: architecture --- p.45 / Chapter 4.3 --- Behavior-based control of Gyrover: case studies --- p.50 / Chapter 4.3.1 --- Vertical balancing --- p.51 / Chapter 4.3.2 --- Tiltup motion --- p.52 / Chapter 4.4 --- Discussions --- p.53 / Chapter 5 --- Implement ation of Learning Control --- p.57 / Chapter 5.1 --- Validation --- p.57 / Chapter 5.1.1 --- Vertical balancing --- p.58 / Chapter 5.1.2 --- Tilt-up motion --- p.62 / Chapter 5.1.3 --- Discussions --- p.62 / Chapter 5.2 --- Implementation --- p.65 / Chapter 5.2.1 --- Vertical balanced motion --- p.65 / Chapter 5.2.2 --- Tilt-up motion --- p.68 / Chapter 5.3 --- Combined motion --- p.70 / Chapter 5.4 --- Discussions --- p.72 / Chapter 6 --- Shared Control --- p.74 / Chapter 6.1 --- Concept --- p.74 / Chapter 6.2 --- Schemes --- p.78 / Chapter 6.2.1 --- Switch mode --- p.79 / Chapter 6.2.2 --- Distributed mode --- p.79 / Chapter 6.2.3 --- Combined mode --- p.80 / Chapter 6.3 --- Shared control of Gyrover --- p.81 / Chapter 6.4 --- How to share --- p.83 / Chapter 6.5 --- Experimental study --- p.88 / Chapter 6.5.1 --- Heading control --- p.89 / Chapter 6.5.2 --- Straight path --- p.90 / Chapter 6.5.3 --- Circular path --- p.91 / Chapter 6.5.4 --- Point-to-point navigation --- p.94 / Chapter 6.6 --- Discussions --- p.95 / Chapter 7 --- Conclusion --- p.103 / Chapter 7.1 --- Contributions --- p.103 / Chapter 7.2 --- Future work --- p.104

For robotic manipulation tasks in uncertain environments, research typically revolves around developing the best possible software control strategy. However, the passive dynamics of the mechanical system, including inertia, stiffness, damping and torque limits, often impose performance limitations that cannot be overcome with software control. Discussions about the passive dynamics are often imprecise, lacking comprehensive details about the physical limitations. In the first half of this paper, we develop relationships between an actuator's passive dynamics and the resulting performance, to better understanding how to tune the passive dynamics. We characterize constant-contact physical interaction tasks into two different tasks that can be roughly approximated as force control and position control and calculate the required input to produce a desired output. These exact solutions provide a basis for understanding how the parameters of the mechanical system affect the overall system's bandwidth limit without limitations of a specific control algorithm. We then present our experimental results compared to the analytical prediction for each task using a bench top actuator. Our analytical and experimental results show what, until now, has only been intuitively understood: soft systems are better at force control, stiff systems are better at position control, and there is no way to optimize an actuator for both tasks. / Graduation date: 2012

We study vertical jumping in a simple robot comprising an actuated mass spring arrangement. The actuator frequency and phase are systematically varied to find optimal performance. Optimal jumps occur above and below (but not at) the robot's resonant frequency f0. Two distinct jumping modes emerge: a simple jump which is optimal above f0 is achievable with a squat maneuver, and a peculiar stutter jump which is optimal below f0 is generated with a countermovement. A simple dynamical model reveals how optimal lift-off results from non-resonant transient dynamics.

The effectiveness of linear control of a planar manipulator is presented for robot operation markedly exceeding the limits of linearity assumed in the design of the linear controller. Wolovich's frequency domain pole placement algorithm is utilized to derive the linear controller. The control scheme must include state estimation since only link position is measured in the planar manipulator studied. Extensive simulations have been conducted not only to verify the linear control design but also to examine the behavior of the controlled system when inputs greatly exceed those assumed for linear design. The results from these studies indicate the linear model performs exactly as designed. The non-linear realistic simulation reveals that the linear model results are obtained when the inputs do not exceed linearity limits. However, when large inputs are applied, the nature of the system response changes significantly. Regardless of the change in behavior, for the cases considered, there was no instability detected and steady-state values were realized with reasonable settling times which increased in length as the size of the inputs were increased. From the simulation results, it is concluded that the linear controller scheme studied is suitable for use in moving objects from one position to another but would not work well in the rapid drawing of lines and curves. / Graduation date: 1992

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Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Howard, Ayanna; Committee Member: Egerstedt, Magnus; Committee Member: Vela, Patricio. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Novel algorithms in robot inverse kinematics and path planning are proposed. Emphasis is placed on real-time execution speed with multiprocessors and adaptability to unpredictable environments. The inverse kinematics algorithm is an iterative solution which is applicable to many classes of industrial robots, and is stable at and around singularities. The method is based on a simple functional analysis of each link of a manipulator and projecting vectors on the coordinate frame of each joint. Heuristic rules are used to control a mobile manipulator base and to guide the manipulator in the case of non-convergence caused by joint limits. The path planning algorithm uses a potential surface in a quantized configuration space. Paths are guaranteed to be collision-free for all parts of the robot. Local minimum regions on the potential surface are filled on demand by extending the obstacles. Arbitrarily shaped obstacles in 3-dimensions can be handled. Using a hierarchical collision detection technique, high execution speed can be maintained even with many complex shaped obstacles in the workspace. The path planning method can theoretically be applied to any manipulator with any degrees of freedom. The implementation of the inverse kinematics and path planning algorithms in a parallel hierarchical multiprocessor computer structure designed for the control of robots is proposed and investigated. Communication among the processors is by point-to-point message passing via asynchronous serial links with message buffers. Computer simulations are used to demonstrate the appropriateness and feasibility of this computer structure for robot control. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate