91 research outputs found
Humanoid Robots
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 vertebral column, compliance and semi-passive dynamics in a lightweight robot
International audienceThis paper presents the humanoid robot Acroban. We study two main issues: 1) Compliance and semi-passive dynamics for locomotion of humanoid robots regarding robustness against unknown external perturbations; 2) The advantages of a bio-inspired multi-articulated vertebral column. We combine mechatronic compliance with structural compliance due to the use of flexible materials. And we explore how these capabilities allow to enforce morphological computation in the design of robust dynamic locomotion. We also investigate the use of compliance to design semi-passive motor primitives using the torso and the arms as a system of accumulation/release of potential/kinetic energy
Biped locomotion control through a biologically-inspired closed-loop controller
Dissertação de mestrado integrado em Engenharia BiomédicaCurrently motor disability in industrialized countries due to neural and physical impairments
is an increasingly worrying phenomenon and the percentage of patients is expected
to be increasing continuously over the coming decades due to a process of ageing the world
is undergoing. Additionally, rising retirement ages, higher demand of elderly people for an
independent, dignified life and mobility, huge cost in the provision of health care are some
other determinants that motivate the restoration of motor function as one of the main goals of
rehabilitation. Modern concepts of motor learning favor a task-specific training in which all
movements in daily life should be trained/assisted repetitively in a physically correct fashion.
Considering the functional activity of the neuronal circuits within the spinal cord, namely
the central pattern generator (CPG), as the foundation to human locomotion, motor relearning
should be based on intensive training strategies directed to the stimulation and reorganization
of such neural pathways through mechanisms addressed by neural plasticity. To this
end, neuromodelings are required to simulate the human locomotion control to overcome the
current technological challenges such as developing smaller, intelligent and cost-effective
devices for home and work rehabilitation scenarios which can enable a continuous therapy/
assistance to guide the impaired limbs in a gentle manner, avoiding abrupt perturbations
and providing as little assistance as necessary. Biomimetic models, taking neurological and
biomechanical inspiration from biological animals, have been embracing these challenges
and developing effective solutions on refining the locomotion models in terms of energy
efficiency, simplicity in the structure and robust adaptability to environment changes and
unexpected perturbations.
Thus, the aim target of this work is to study the applicability of the CPG model for
gait rehabilitation, either for assistance and/or therapy purposes. Focus is developed on the
locomotion control to increase the knowledge of the underlying principles useful for gait
restoration, exploring the brainstem-spinal-biomechanics interaction more fully. This study
has great application in the project of autonomous robots and in the rehabilitation technology,
not only in the project of prostheses and orthoses, but also in the searching of procedures that
help to recuperate motor functions of human beings.
Encouraging results were obtained which pave the way towards the simulation of more
complex behaviors and principles of human locomotion, consequently contributing for improved
automated motor rehabilitation adapted to the rehabilitation emerging needs.Actualmente a debilidade motora em países industrializados devido a deficiências neurais
e físicas é um fenómeno crescente de apreensão sendo expectável um contínuo aumento do
rácio de pacientes nas próximas décadas devido ao processo de envelhecimento. Inclusivé,
o aumento da idade de reforma, a maior procura por parte dos idosos para uma mobilidade
e vida autónoma e condigna, o elevado custo nos cuidados de saúde são incentivos para a
restauração da função motora como um dos objectivos principais da reabilitação. Conceitos
recentes de aprendizagem motora apoiam um treino de tarefas específicas no qual movimentos
no quotidiano devem ser treinados/assistidos de forma repetitiva e fisicamente correcta.
Considerando a actividade funcional dos circuitos neurais na medula, nomeadamente
o gerador de padrão central (CPG), como a base da locomoção, a reaprendizagem motora
deve-se basear em estratégias intensivas de treino visando a estimulação e reorganização
desses vias neurais através de mecanismos abordados pela plasticidade neural. Assim,
são necessários modelos neurais para simular o controlo da locomoção humana de modo
a superar desafios tecnológicos actuais tais como o desenvolvimento de dispositivos mais
compactos, inteligentes e económicos para os cenários de reabilitação domiciliar e laboral
que podem permitir uma terapia/assistência contínua na guia dos membros debilitados de
uma forma suave, evitando perturbações abruptas e fornecendo assistência na medida do
necessário. Modelos biomiméticos, inspirando-se nos princípios neurológicos e biomecânicos
dos animais, têm vindo a abraçar esses desafios e a desenvolver soluções eficazes na
refinação de modelos de locomoção em termos da eficiência de energia, da simplicidade na
estrutura e da adaptibilidade robusta face a alterações ambientais e perturbações inesperadas.
Então, o objectivo principal do trabalho é estudar a aplicabilidade do modelo de CPG para
a reabilitação da marcha, para efeitos de assistência e/ou terapia. É desenvolvido um foco no
controlo da locomoção para maior entendimento dos princípios subjacentes úteis para a recuperação
da marcha, explorando a interacção tronco cerebral-espinal medula-biomecânica de
forma mais detalhada. Este estudo tem potencial aplicação no projecto de robôs autónomos
e na tecnologia de reabilitação, não só no desenvolvimento de ortóteses e próteses, mas também
na procura de procedimentos úteis para a recuperação da função motora.
Foram obtidos resultados promissores susceptíveis de abrir caminho à simulação de comportamentos
e princípios mais complexos da marcha, contribuindo consequentemente para
uma aprimorada reabilitação motora automatizada adaptada às necessidades emergentes
Climbing and Walking Robots
With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information
Bio-Inspired Robotics
Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field
Locomotion through morphology, evolution and learning for legged and limbless robots
Mención Internacional en el título de doctorRobot locomotion is concerned with providing autonomous locomotion capabilities to mobile robots. Most current day robots feature some form of locomotion for navigating in their environment.
Modalities of robot locomotion includes: (i) aerial locomotion, (ii) terrestrial locomotion, and (iii) aquatic locomotion (on or under water). Three main forms of terrestrial locomotion are, legged locomotion, limbless locomotion and wheel-based locomotion. A Modular Robot (MR), on the other hand, is a robotic system composed of several independent unit modules, where, each module is a robot by itself. The objective in this thesis is to develop legged locomotion in a humanoid robot, as well as, limbless locomotion in modular robotic configurations. Taking inspiration from biology, robot locomotion from the perspective of robot’s morphology, through evolution, and through learning are investigated in this thesis.
Locomotion is one of the key distinguishing characteristics of a zoological organism. Almost all animal species, and even some plant species, produce some form of locomotion. In the past few years, robots have been “moving out” of the factory floor and research labs, and are becoming increasingly common in everyday life. So, providing stable and agile locomotion capabilities for robots to navigate a wide range of environments becomes pivotal. Developing locomotion in robots through biologically inspired methods, also facilitates furthering our understanding on how biological processes may function.
Connected modules in a configuration, exert force on each other as a result of interaction between each other and their environment. This phenomenon is studied and quantified, and then used as implicit communication between robot modules for producing locomotion coordination in MRs. Through this, a strong link between robot morphology and the gait that emerge in it is established.
A variety of locomotion controller, some periodic-function based and some morphology based, are developed for MR locomotion and bipedal gait generation. A hybrid Evolutionary
Algorithm (EA) is implemented for evolving gaits, both in simulation as well as in the real-world on a physical modular robotic configuration. Limbless gaits in MRs are also learnt by learning optimal control policies, through Reinforcement Learning (RL).En robótica, la locomoción trata de proporcionar capacidades de locomoción autónoma a robots móviles. La mayoría de los robots actuales tiene alguna forma de locomoción para navegar en su entorno. Los modos de locomoción robótica se pueden repartir entre: (i) locomoción aérea, (ii) locomoción terrestre, y (iii) locomoción acuática (sobre o bajo el agua). Las tres formas básicas de locomoción terrestre son la locomoción mediante piernas, la locomoción sin miembros, y la locomoción basada en ruedas. Un Robot Modular, por otra parte, es un sistema robótico compuesto por varios módulos independientes, donde cada módulo es un robot en sí mismo.
El objetivo de esta tesis es el desarrollo de la locomoción mediante piernas para un robot humanoide, así como el de la locomoción sin miembros para varias configuraciones de robots modulares. Inspirándose en la biología, también se investiga en esta tesis el desarrollo de la locomoción del robot según su morfología, gracias a técnicas de evolución y de aprendizaje.
La locomoción es una de las características distintivas de un organismo zoológico. Casi todas las especies animales, e incluso algunas especies de plantas, poseen algún tipo de locomoción. En los últimos años, los robots han “migrado” desde las fábricas y los laboratorios de investigación, y se están integrando cada vez más en nuestra vida diaria. Por estas razones, es crucial proporcionar capacidades de locomoción estables y ágiles a los robots para que puedan navegar por todo tipo de entornos. El uso de métodos de inspiración biológica para alcanzar esta meta también nos ayuda a entender mejor cómo pueden funcionar los procesos biológicos equivalentes.
En una configuración de módulos conectados, puesto que cada uno interacciona con su entorno, los módulos ejercen fuerza los unos sobre los otros. Este fenómeno se ha estudiado y cuantificado, y luego se ha usado como comunicación implícita entre los módulos para producir la coordinación en la locomoción de este robot. De esta manera, se establece un fuerte vínculo entre la morfología de un robot y el modo de andar que este desarrolla.
Se han desarrollado varios controladores de locomoción para robots modulares y robots bípedos, algunos basados en funciones periódicas, otros en la morfología del robot. Un algoritmo evolutivo híbrido se ha implementado para la evolución de locomociones, tanto en simulación como en el mundo real en una configuración física de robot modular. También se pueden generar locomociones sin miembros para robots modulares, determinando las políticas de control óptimo gracias a técnicas de aprendizaje por refuerzo.
Se presenta en primer lugar en esta tesis el estado del arte de la robótica modular, enfocándose en la locomoción de robots modulares, los controladores, la locomoción bípeda y la computación morfológica. A continuación se describen cinco configuraciones diferentes de robot modular que se utilizan en esta tesis, seguido de cuatro controladores de locomoción. Estos controladores son el controlador heterogéneo, el controlador basado en funciones periódicas, el controlador homogéneo y el controlador basado en la morfología del robot.
Se desarrolla como parte de este trabajo un controlador de locomoción lineal, periódico, basado en features, para la locomoción bípeda de robots humanoides. Los parámetros de control se ajustan primero a mano para reproducir un modelo cart-table, y el controlador se evalúa en un robot humanoide simulado. A continuación, gracias a un algoritmo evolutivo, la optimización de los parámetros de control permite desarrollar una locomoción sin modelo predeterminado.
Se desarrolla como parte de esta tesis un enfoque sobre algoritmos de Embodied Evolución, en otras palabras el uso de robots modulares físicos en la fase de evolución. La implementación material, la configuración experimental, y el Algoritmo Evolutivo implementado para Embodied Evolución, se explican detalladamente.
El trabajo también incluye una visión general de las técnicas de aprendizaje por refuerzo y de los Procesos de Decisión de Markov. A continuación se presenta un algoritmo popular de aprendizaje por refuerzo, llamado Q-Learning, y su adaptación para aprender locomociones de robots modulares. Se proporcionan una implementación del algoritmo de aprendizaje y la evaluación experimental de la locomoción generada.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Antonio Barrientos Cruz.- Secretario: Luis Santiago Garrido Bullón.- Vocal: Giuseppe Carbon
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