98 research outputs found

    Parametrically Excited Dynamic Bipedal Walking

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    Kinematic and dynamic analysis for biped robots design

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    En esta tesis un nuevo método para encontrar sistemas dinámicamente equivalentes es propuesto. El objetivo es el de crear una herramienta para el análisis de robots bípedos. La herramienta consiste en modelos simplificados obtenidos del principio de equivalencia dinámica, que dice que si dos sistemas poseen la misma masa, el mismo centro de masa y el mismo momento de inercia, entonces son dinámicamente equivalentes. Este concepto no es nuevo y es comúnmente utilizado en el diseño de máquinas alternativas, o para encontrar el sweet spot de objetos esbeltos tales como bates o espadas. Con la aplicación del principio de equivalencia dinámica se encuentra el centro de percusión. La aportación en esta tesis es la aplicación de este concepto al análisis de robots bípedos, y la extensión del centro de percusión a cadenas cinemáticas. La herramienta fundamental para la obtención de resultados de investigación en esta tesis hace uso del lenguaje de simulación Modelica®. Las simulaciones son altamente detalladas gracias a la librería estándar Multibody incluida en las especificaciones del mismo. Como consecuencia de los trabajos desarrollados se crearon nuevas clases para extender la capacidad de la librería y aplicarla a m´aquinas caminantes. El desarrollo de esta tesis está centrado en el desarrollo de dos modelos. El primero es un péndulo invertido equivalente, con la característica que posee las mismas propiedades dinámicas del robot que modela. Dichas propiedades son la masas total, el centro de masa y el momento de inercia. Este modelo es luego utilizado para generar el caminar de un bípedo simple. El bípedo es simulado con un volante de inercia como cuerpo, y pies de contacto puntual. Posee rodillas y está totalmente actuado. Los eslabones del robot poseen propiedades de sólido rígido y ninguna simplificación ha sido considerada. El segundo modelo tiene el objetivo de imitar la topología del bípedo que representa, por lo tanto tiene un grado mayor de complejidad que el anterior. Este modelo es construido al dividir al robot en tres grupos: Las dos piernas, y otro grupo compuesto por la cabeza, los brazos y el torso (Denominado HAT por sus siglas en inglés). Este modelo es denominado modelo de cuatro masas puntuales. Este modelo es posteriormente validado utilizándolo para desacoplar la dinámica del sistema, la única información utilizada para llevar a cabo esta tarea es proporcionada por dicho modelo. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------In this thesis a method to find dynamically equivalent systems is proposed. The objective is to provide a tool to analyze biped robots by simplifying their dynamics to simpler models. The equivalent models are obtained with the concept of dynamic equivalence that states that if two systems share the same total mass, the same center of mass, and the same moment of inertia then they are considered to be dynamically equivalent. This concept is not new and it is used in the design of alternative machines, or to find the sweet spot of long object like swords or bats. The result of the application of the dynamic equivalence principle is the point known as the center of percussion. The novelty in this thesis is to apply this concept to the analysis of biped robots, and the extension of the center of percussion to kinematic chains. The work in this thesis developed with the help of the simulation language Modelica®. The simulations are very detailed by implementing elaborated rigid body dynamics provided by the multibody standard library included in the language specifications. New classes were created in order to be able to simulate walking machines. Those classes introduce contact objects at ground foot interactions and mechanical stops for knee joints. The development of this thesis is centered around the proposal of two models. The first model is an equivalent inverted pendulum with the characteristic that it has the same dynamic properties, i.e., total mass, center of mass and moment of inertia, of the biped that models. This model is later used to synthesize gait in a simple, but realistic biped. The biped is simulated with a flywheel body, and point feet. It has knees and it is fully actuated. Also all the links have complete rigid body properties and no simplifications were done. The second model has the objective to resemble the topology of the biped it represents, therefore it is slightly more complex than the equivalent inverted pendulum. This model is constructed by grouping the components of the robot in three groups: Two legs and the HAT group (HAT stands for head, arms and trunk). This model is denominated four point masses model. The model is later validated by decoupling the dynamics of the system only with the information provided by the four point masses model

    Robust Cascade Controller for Nonlinearly Actuated Biped Robots: Experimental Evaluation

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    In this paper we consider the postural stability problem for nonlinearly actuated quasi-static biped robots, both with respect to the joint angular positions and also with reference to the gripping effect between the foot/feet against the ground during robot locomotion. Zero moment point based mathematical models are developed to establish a relationship between the robot state variables and the stability margin of the foot (feet) contact surface and the supporting ground. Then, in correspondence with the developed dynamical model and its associated uncertainty, and in the presence of non-modeled robot mechanical structure vibration modes, we propose a robust control architecture that uses two cascade regulators. The overall robust control system consists of a nonlinear robust variable structure controller in an inner feedback loop for joint trajectory tracking, and anH∞ linear robust regulator in an outer, direct zero moment point feedback loop to ensure the foot-ground contact stability. The effectiveness of this cascade controller is evaluated using a simplified prototype of a nonlinearly actuated biped robot in double support placed on top of a one-degree-of-freedom mobile platform and subjected to external disturbances. The achieved experimental results have revealed that the simplified prototype is successfully stabilized.In this paper we consider the postural stability problem for nonlinearly actuated quasi-static biped robots, both with respect to the joint angular positions and also with reference to the gripping effect between the foot/feet against the ground during robot locomotion. Zero moment point based mathematical models are developed to establish a relationship between the robot state variables and the stability margin of the foot (feet) contact surface and the supporting ground. Then, in correspondence with the developed dynamical model and its associated uncertainty, and in the presence of non-modeled robot mechanical structure vibration modes, we propose a robust control architecture that uses two cascade regulators. The overall robust control system consists of a nonlinear robust variable structure controller in an inner feedback loop for joint trajectory tracking, and anH∞ linear robust regulator in an outer, direct zero moment point feedback loop to ensure the foot-ground contact stability. The effectiveness of this cascade controller is evaluated using a simplified prototype of a nonlinearly actuated biped robot in double support placed on top of a one-degree-of-freedom mobile platform and subjected to external disturbances. The achieved experimental results have revealed that the simplified prototype is successfully stabilized

    Intelligent approaches in locomotion - a review

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    Standing Posture Modeling and Control for a Humanoid Robot

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    Master'sMASTER OF ENGINEERIN

    Fast Model Identification via Physics Engines for Data-Efficient Policy Search

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    This paper presents a method for identifying mechanical parameters of robots or objects, such as their mass and friction coefficients. Key features are the use of off-the-shelf physics engines and the adaptation of a Bayesian optimization technique towards minimizing the number of real-world experiments needed for model-based reinforcement learning. The proposed framework reproduces in a physics engine experiments performed on a real robot and optimizes the model's mechanical parameters so as to match real-world trajectories. The optimized model is then used for learning a policy in simulation, before real-world deployment. It is well understood, however, that it is hard to exactly reproduce real trajectories in simulation. Moreover, a near-optimal policy can be frequently found with an imperfect model. Therefore, this work proposes a strategy for identifying a model that is just good enough to approximate the value of a locally optimal policy with a certain confidence, instead of wasting effort on identifying the most accurate model. Evaluations, performed both in simulation and on a real robotic manipulation task, indicate that the proposed strategy results in an overall time-efficient, integrated model identification and learning solution, which significantly improves the data-efficiency of existing policy search algorithms.Comment: IJCAI 1

    Goal-Based Control and Planning in Biped Locomotion Using Computational Intelligence Methods

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    Este trabajo explora la aplicación de campos neuronales, a tareas de control dinámico en el domino de caminata bípeda. En una primera aproximación, se propone una arquitectura de control que usa campos neuronales en 1D. Esta arquitectura de control es evaluada en el problema de estabilidad para el péndulo invertido de carro y barra, usado como modelo simplificado de caminata bípeda. El controlador por campos neuronales, parametrizado tanto manualmente como usando un algoritmo evolutivo (EA), se compara con una arquitectura de control basada en redes neuronales recurrentes (RNN), también parametrizada por por un EA. El controlador por campos neuronales parametrizado por EA se desempeña mejor que el parametrizado manualmente, y es capaz de recuperarse rápidamente de las condiciones iniciales más problemáticas. Luego, se desarrolla una arquitectura extendida de control y planificación usando campos neurales en 2D, y se aplica al problema caminata bípeda simple (SBW). Para ello se usa un conjunto de valores _óptimos para el parámetro de control, encontrado previamente usando algoritmos evolutivos. El controlador óptimo por campos neuronales obtenido se compara con el controlador lineal propuesto por Wisse et al., y a un controlador _optimo tabular que usa los mismos parámetros óptimos. Si bien los controladores propuestos para el problema SBW implementan una estrategia activa de control, se aproximan de manera más cercana a la caminata dinámica pasiva (PDW) que trabajos previos, disminuyendo la acción de control acumulada. / Abstract. This work explores the application of neural fields to dynamical control tasks in the domain of biped walking. In a first approximation, a controller architecture that uses 1D neural fields is proposed. This controller architecture is evaluated using the stability problem for the cart-and-pole inverted pendulum, as a simplified biped walking model. The neural field controller is compared, parameterized both manually and using an evolutionary algorithm (EA), to a controller architecture based on a recurrent neural neuron (RNN), also parametrized by an EA. The non-evolved neural field controller performs better than the RNN controller. Also, the evolved neural field controller performs better than the non-evolved one and is able to recover fast from worst-case initial conditions. Then, an extended control and planning architecture using 2D neural fields is developed and applied to the SBW problem. A set of optimal parameter values, previously found using an EA, is used as parameters for neural field controller. The optimal neural field controller is compared to the linear controller proposed by Wisse et al., and to a table-lookup controller using the same optimal parameters. While being an active control strategy, the controllers proposed here for the SBW problem approach more closely Passive Dynamic Walking (PDW) than previous works, by diminishing the cumulative control action.Maestrí
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