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

This dissertation deals with the control, guidance and stabilisation of nonlinear, non¬holonomic systems. It is shown that the kinematics of the system can be separated from the dynamics of the system by using successively two inverse dynamics type of transformations. This leads to a linear decoupled kinematical system, control strategies can then be developed that directly control the motion of the system. The method is applied to a system which is composed of a disk rolling on a plane, a controlled slender rod that is pivoted through its center of mass about the disk's center and two overhead rotors with their axes fixed in the upper part of the rod. Control strategies are designed under which the disk's inclination is stabilised about its vertical position and the disk's motion is able to asymptotically track any given smooth ground trajectory. The control strategy is shown to be stable in the presence parametric uncertainties. It was furthermore shown that the system is path controllable. Finally an extended inverse dynamics control law is introduced which deals directly with underactuated systems. An example of an articulated crane is solved using extended inverse dynamics control. Feasible control is used to ensure that the internal dynamics of the system remains bounded and that the crane reach its desired final position in a given time interval [O, tƒ]. / Dissertation (MSc (Applied SCience))--University of Pretoria, 2007. / Electrical, Electronic and Computer Engineering / unrestricted

Colloidal robots refer to the colloid scale (from nm to μm) machines capable of carrying out programmed actions for complex tasks automatically. Because of its promising application in engineering and medical service, colloidal robotics have been of much recent research interest in both theoretical and technological relevance. However, there remain many open challenges on increasing actuation efficiency, achieving high level tasks (e.g., autonomous navigation), etc. This dissertation, in general, focuses on developing new actuation mechanisms and designing autonomous navigation strategies for colloidal robots with both experimental and computational efforts. Firstly, the motivation, background and recent research advances on colloidal robots are reviewed. In Chapter 2, a high-efficiency actuation method called contact charge electrophoresis(CCEP) is introduced to propel the dielectric metallic Janus colloid particles. The autonomous propulsion of Janus particles shows colloidal particle asymmetries can be used to direct the motions of colloidal robots. Beyond single colloidal particle's propulsion, Chapter 3 shows multi-colloidal particles' motions can be coupled and synchronized to generate traveling waves via electrostatic interactions. Our results in Chapter 3 suggest that simple energy inputs can coordinate complex motions for colloidal robots. Then inspired by active particles motions' guided by their symmetry in Chapter 2, we show in Chapter 4 how multiple autonomous navigation can be achieved by designing the active particle's geometry and its stimulus response. Chapter 4 describes a strategy that colloid particles can sense the stimulus in environment via shape-shifting. The feedback loop of sensing and motion enables colloid particles to achieve positive or negative chemotaxis-like navigation. To experimentally realize similar navigation behaviors introduced in Chapter 4, we described a magnetic driven colloidal robot system in Chapter 5, which could show navigation behaviors (uphill and downhill) on a slope by rationally programming the external magnetic field. Chapter 6 highlights future research directions and potential applications of colloidal robots.

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High-performing legged robots require complex spatial leg designs and controllers to simultaneously implement propulsion, maneuvering and stabilization behaviors. Looking to nature, tails assist a variety of animals with these functionalities separate from the animals' legs. However, prior research into robotic tails primarily focuses on single-mass pendulums driven in a single plane of motion and designed to perform a specific task. In order to justify including a robotic tail on-board a legged robot, the tail should be capable of performing multiple functionalities in the robot's yaw, pitch and roll directions. The aim of this research is to study bioinspired articulated spatial robotic tails capable of implementing maneuvering and stabilization behaviors in quadrupedal and bipedal legged robots. To this end, two novel serpentine tails designs are presented and integrated into prototypes to test their maneuvering and stabilizing capabilities. Dynamic models for these two tail designs are formulated, along with the dynamic model of a previously considered continuum robot, to predict the tails' motion and the loading they will apply on their legged robots. To implement the desired behaviors, outer- and inner-loop controllers are formulated for the serpentine tails: the outer-loop controllers generate the desired tail trajectory to maneuver or stabilize the legged robot, and the inner-loop controllers calculate control inputs for the tail that implement the desired tail trajectory using feedback linearization. Maneuvering and stabilizing case studies are generated to demonstrate the tails' ability to: (1) generate yaw angle turning in both a quadruped and a biped, (2) improve the quadruped's ability to reject an externally applied roll moment disturbance that would otherwise destabilize it, and (3) counteract the biped's roll angle instability when it lifts one of its legs (for example, during its gait cycle). Tail simulations and experimental results are used to implement these case studies in conjunction with multi-body dynamic simulations of the quadrupedal and bipedal legged platforms. Results successfully demonstrate the tails' ability to maneuver and stabilize legged robots, and provide a firm foundation for future work implementing a tailed-legged robot. / Ph. D.

Bipedal robots offer a uniquely flexible platform capable of navigating complex, human-centric environments. This makes them ideally suited for a variety of missions, including disaster response and relief, emergency scenarios, or exoskeleton systems for individuals with disabilities. This, however, requires significant advances in humanoid locomotion and control, as they are still slow, unnatural, inefficient, and relatively unstable. The work of this dissertation the state of the art with the aim was of increasing the robustness and efficiency of these bipedal walking platforms. We present a series of control improvements to enable reliable, robust, natural bipedal locomotion that was validated on a variety of bipedal robots using both hardware and simulation experiments. A huge part of reliable walking involves maximizing the robot's control authority. We first present the development of a model predictive controller to both control the ground reaction forces and perform step adjustment for walking stabilization using a mixed-integer quadratic program. This represents the first model predictive controller to include step rotation in the optimization and leverage the capabilities of the time-varying divergent component of motion for navigating rough terrain. We also analyze the potential capabilities of model predictive controllers for the control of bipedal walking. As an alternative to standard trajectory optimization-based model predictive controls, we present several optimization-based control schemes that leverage more traditional bipedal walking control approaches by embedding a proportional feedback controller into a quadratic program. This controller is capable of combining multiple feedback mechanisms: ground reaction feedback (the "ankle strategy"), angular momentum (the "hip strategy"), swing foot speed up, and step adjustment. This allows the robot to effectively shift its weight, pitch its torso, and adjust its feet to retain balance, while considering environmental constraints, when available. To enable the robot to walk with straightened legs, we present a strategy that insures that the dynamic plans are kinematically and dynamically feasible to execute using straight legs. The effects of timing on dynamic plans are typically ignored, resulting in them potentially requiring significantly bending the legs during execution. This algorithm modifies the step timings to insure the plan can be executed without bending the legs beyond certain angle, while leaving the desired footsteps unmodified. To then achieve walking with straight legs we then presented a novel approach for indirectly controlling the center of mass height through the leg angles. This avoids complicated height planning techniques that are both computationally expensive and often not general enough to consider variable terrain by effectively biasing the solution of the whole-body controller towards using straighter legs. To incorporate the toe-off motion that is essential to both natural and straight leg walking, we also present a strategy for toe-off control that allows it to be an emergent behavior of the whole-body controller. The proposed approach was demonstrated through a series of simulation and experimental results on a variety of platforms. Model predictive control for step adjustment and rough terrain is illustrated in simulation, while the other step adjustment strategies and straight leg walking approaches are presented recovering from external disturbances and walking over a variety of terrains in hardware experiments. We discuss many of the practical considerations and limitations required when porting simulation-based controller development to hardware platforms. Using the presented approaches, we also demonstrated a important concept: using whole-body control frameworks, not every desired motion need be directly commanded. Many of these motions, such as toe-off, may simply be emergent behaviors that result by attempting to satisfy other objectives, such as desired reaction forces. We also showed that optimization is a very powerful tool for walking control, able to determine both stabilizing inputs and joint torques. / Ph. D.

L'architecture mécanique, l'actionnement, la détection directe ou indirecte des efforts ainsi que la conception de contrôleurs en impédance ou en admittance sont les aspects fondamentaux et importants à considérer pour le développement d'un robot permettant une interaction physique humain-robot (IPHR) sécuritaire. Cette thèse est consacrée au développement de nouvelles architectures de robots pour l'IPHR qui ont une structure simple, peu ou pas de singularités, qui sont légers et à faible impédance mécanique. Un nouveau robot parallèle hybride cinématiquement redondant (RPHCR) sans singularité dans l'espace de travail et ayant une faible inertie mobile est d'abord proposé. Le concept de la redondance cinématique des membrures et l'agencement d'assemblage de la plate-forme mobile de ce robot sont ensuite généralisés et développés en une méthodologie pour la synthèse de nouveaux RPHCRs. Plusieurs exemples d'architectures sont présentés et une solution analytique du problème géométrique inverse est obtenue. Le problème géométrique direct des RPHCRs doit être résolu afin de déterminer la position et l'orientation de la plate-forme mobile pour des coordonnées articulaires données. Différentes approches pour résoudre le problème géométrique direct sont alors proposées. Il est montré que le problème géométrique direct des RPHCRs proposés dans la thèse est beaucoup plus simple que celui associé aux robots non redondants ou à de nombreux autres robots parallèles cinématiquement redondants. L'agrandissement de l'espace de travail et l'optimisation des trajectoires articulaires des RPHCRs sont réalisés en déterminant les valeurs optimales des coordonnées redondantes. Enfin, la redondance est en outre utilisée pour opérer un préhenseur monté sur la plateforme mobile à partir des actionneurs fixés à la base du robot ou près de celle-ci. Un contrôleur combiné en position et force de préhension est proposé pour le contrôle de la force de préhension. / Robot architecture, actuation, indirect/direct force sensing, and impedance/admittance controller design are the fundamental and important aspects to be considered in order to achieve safe physical human-robot interaction (pHRI). This thesis is devoted to the development of novel robot architectures for pHRI that have a simple structure, few or no singularities, lightweight, and low-impedance. A novel kinematically redundant hybrid parallel robot (KRHPR) that is singularity-free throughout the workspace and has low moving inertia is firstly proposed. The concept of the redundant links and moving platform assembly arrangement of this robot is further generalised and developed into a methodology for the synthesis of novel KRHPRs. Several example architectures are presented and an analytical inverse kinematic solution is derived.The forward kinematics of the KRHPRs must be solved to determine the position and orientation of the moving platform for given joint coordinates. Different approaches for solving the forward kinematic problem are then proposed. It is shown that the forward kinematics of the KRHPRs proposed in the thesis is much simpler than that of their non-redundant counterparts or that of many other kinematically redundant parallel robots. Workspace enlargement and joint trajectory optimisation of the KRHPRs are pursued by determining the optimal values of the redundant coordinates. Finally, the redundancy is further utilised to operate a gripper on the moving platform from the base actuators. A combined position and grasping force controller is proposed for the control of the grasping force.