865 research outputs found

    Intelligent approaches in locomotion - a review

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    Development of a Rat-like Robot and Its Applications in Animal Behavior Research

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    制度:新 ; 報告番号:甲3587号 ; 学位の種類:博士(工学) ; 授与年月日:2012/3/15 ; 早大学位記番号:新592

    Humanoid Robots

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    For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

    Bio-inspired kinematical control of redundant robotic manipulators

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    Purpose – This paper aims to propose an innovative kinematic control algorithm for redundant robotic manipulators. The algorithm takes advantage of a bio-inspired approach. Design/methodology/approach – A simplified two-degree-of-freedom model is presented to handle kinematic redundancy in the x-y plane; an extension to three-dimensional tracking tasks is presented as well. A set of sample trajectories was used to evaluate the performances of the proposed algorithm. Findings – The results from the simulations confirm the continuity and accuracy of generated joint profiles for given end-effector trajectories as well as algorithm robustness, singularity and self-collision avoidance. Originality/value – This paper shows how to control a redundant robotic arm by applying human upper arm-inspired concept of inter-joint dependency

    Reinforcement Learning Algorithms in Humanoid Robotics

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    Humanoid robot control of complex postural tasks based on learning from demostration

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    Mención Internacional en el título de doctorThis thesis addresses the problem of planning and controlling complex tasks in a humanoid robot from a postural point of view. It is motivated by the growth of robotics in our current society, where simple robots are being integrated. Its objective is to make an advancement in the development of complex behaviors in humanoid robots, in order to allow them to share our environment in the future. The work presents different contributions in the areas of humanoid robot postural control, behavior planning, non-linear control, learning from demonstration and reinforcement learning. First, as an introduction of the thesis, a group of methods and mathematical formulations are presented, describing concepts such as humanoid robot modelling, generation of locomotion trajectories and generation of whole-body trajectories. Next, the process of human learning is studied in order to develop a novel method of postural task transference between a human and a robot. It uses the demonstrated action goal as a metrics of comparison, which is codified using the reward associated to the task execution. As an evolution of the previous study, this process is generalized to a set of sequential behaviors, which are executed by the robot based on human demonstrations. Afterwards, the execution of postural movements using a robust control approach is proposed. This method allows to control the desired trajectory even with mismatches in the robot model. Finally, an architecture that encompasses all methods of postural planning and control is presented. It is complemented by an environment recognition module that identifies the free space in order to perform path planning and generate safe movements for the robot. The experimental justification of this thesis was developed using the humanoid robot HOAP-3. Tasks such as walking, standing up from a chair, dancing or opening a door have been implemented using the techniques proposed in this work.Esta tesis aborda el problema de la planificación y control de tareas complejas de un robot humanoide desde el punto de vista postural. Viene motivada por el auge de la robótica en la sociedad actual, donde ya se están incorporando robots sencillos y su objetivo es avanzar en el desarrollo de comportamientos complejos en robots humanoides, para que en el futuro sean capaces de compartir nuestro entorno. El trabajo presenta diferentes contribuciones en las áreas de control postural de robots humanoides, planificación de comportamientos, control no lineal, aprendizaje por demostración y aprendizaje por refuerzo. En primer lugar se desarrollan un conjunto de métodos y formulaciones matemáticas sobre los que se sustenta la tesis, describiendo conceptos de modelado de robots humanoides, generación de trayectorias de locomoción y generación de trayectorias del cuerpo completo. A continuación se estudia el proceso de aprendizaje humano, para desarrollar un novedoso método de transferencia de una tarea postural de un humano a un robot, usando como métrica de comparación el objetivo de la acción demostrada, que es codificada a través del refuerzo asociado a la ejecución de dicha tarea. Como evolución del trabajo anterior, se generaliza este proceso para la realización de un conjunto de comportamientos secuenciales, que son de nuevo realizados por el robot basándose en las demostraciones de un ser humano. Seguidamente se estudia la ejecución de movimientos posturales utilizando un método de control robusto ante imprecisiones en el modelado del robot. Para analizar, se presenta una arquitectura que aglutina los métodos de planificación y el control postural desarrollados en los capítulos anteriores. Esto se complementa con un módulo de reconocimiento del entorno y extracción del espacio libre para poder planificar y generar movimientos seguros en dicho entorno. La justificación experimental de la tesis se ha desarrollado con el robot humanoide HOAP-3. En este robot se han implementado tareas como caminar, levantarse de una silla, bailar o abrir una puerta. Todo ello haciendo uso de las técnicas propuestas en este trabajo.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Manuel Ángel Armada Rodríguez.- Secretario: Luis Santiago Garrido Bullón.- Vocal: Sylvain Calino

    Comparative evaluation of approaches in T.4.1-4.3 and working definition of adaptive module

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    The goal of this deliverable is two-fold: (1) to present and compare different approaches towards learning and encoding movements us- ing dynamical systems that have been developed by the AMARSi partners (in the past during the first 6 months of the project), and (2) to analyze their suitability to be used as adaptive modules, i.e. as building blocks for the complete architecture that will be devel- oped in the project. The document presents a total of eight approaches, in two groups: modules for discrete movements (i.e. with a clear goal where the movement stops) and for rhythmic movements (i.e. which exhibit periodicity). The basic formulation of each approach is presented together with some illustrative simulation results. Key character- istics such as the type of dynamical behavior, learning algorithm, generalization properties, stability analysis are then discussed for each approach. We then make a comparative analysis of the different approaches by comparing these characteristics and discussing their suitability for the AMARSi project

    Development of Cognitive Capabilities in Humanoid Robots

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    Merged with duplicate record 10026.1/645 on 03.04.2017 by CS (TIS)Building intelligent systems with human level of competence is the ultimate grand challenge for science and technology in general, and especially for the computational intelligence community. Recent theories in autonomous cognitive systems have focused on the close integration (grounding) of communication with perception, categorisation and action. Cognitive systems are essential for integrated multi-platform systems that are capable of sensing and communicating. This thesis presents a cognitive system for a humanoid robot that integrates abilities such as object detection and recognition, which are merged with natural language understanding and refined motor controls. The work includes three studies; (1) the use of generic manipulation of objects using the NMFT algorithm, by successfully testing the extension of the NMFT to control robot behaviour; (2) a study of the development of a robotic simulator; (3) robotic simulation experiments showing that a humanoid robot is able to acquire complex behavioural, cognitive, and linguistic skills through individual and social learning. The robot is able to learn to handle and manipulate objects autonomously, to cooperate with human users, and to adapt its abilities to changes in internal and environmental conditions. The model and the experimental results reported in this thesis, emphasise the importance of embodied cognition, i.e. the humanoid robot's physical interaction between its body and the environment
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