99 research outputs found
Neuro-mechanical entrainment in a bipedal robotic walking platform
In this study, we investigated the use of van der Pol oscillators in a 4-dof embodied bipedal robotic platform for the purposes of planar walking. The oscillator controlled the hip and knee joints of the robot and was capable of generating waveforms with the correct frequency and phase so as to entrain with the mechanical system. Lowering its oscillation frequency resulted in an increase to the walking pace, indicating exploitation of the global natural dynamics. This is verified by its operation in absence of entrainment, where faster limb motion results in a slower overall walking pace
Neuro-mechanical entrainment in a bipedal robotic walking platform
In this study, we investigated the use of van der Pol oscillators in a 4-dof embodied bipedal robotic platform for the purposes of planar walking. The oscillator controlled the hip and knee joints of the robot and was capable of generating waveforms with the correct frequency and phase so as to entrain with the mechanical system. Lowering its oscillation frequency resulted in an increase to the walking pace, indicating exploitation of the global natural dynamics. This is verified by its operation in absence of entrainment, where faster limb motion results in a slower overall walking pace
Chaotic exploration and learning of locomotion behaviours
We present a general and fully dynamic neural system, which exploits intrinsic chaotic dynamics, for the real-time goal-directed exploration and learning of the possible locomotion patterns of an articulated robot of an arbitrary morphology in an unknown environment. The controller is modeled as a network of neural oscillators that are initially coupled only through physical embodiment, and goal-directed exploration of coordinated motor patterns is achieved by chaotic search using adaptive bifurcation. The phase space of the indirectly coupled neural-body-environment system contains multiple transient or permanent self-organized dynamics, each of which is a candidate for a locomotion behavior. The adaptive bifurcation enables the system orbit to wander through various phase-coordinated states, using its intrinsic chaotic dynamics as a driving force, and stabilizes on to one of the states matching the given goal criteria. In order to improve the sustainability of useful transient patterns, sensory homeostasis has been introduced, which results in an increased diversity of motor outputs, thus achieving multiscale exploration. A rhythmic pattern discovered by this process is memorized and sustained by changing the wiring between initially disconnected oscillators using an adaptive synchronization method. Our results show that the novel neurorobotic system is able to create and learn multiple locomotion behaviors for a wide range of body configurations and physical environments and can readapt in realtime after sustaining damage
Fast biped walking with a neuronal controller and physical computation
Biped walking remains a difficult problem and robot models can
greatly {facilitate} our understanding of the underlying
biomechanical principles as well as their neuronal control. The
goal of this study is to specifically demonstrate that stable
biped walking can be achieved by combining the physical properties
of the walking robot with a small, reflex-based neuronal network,
which is governed mainly by local sensor signals. This study shows
that human-like gaits emerge without {specific} position or
trajectory control and that the walker is able to compensate small
disturbances through its own dynamical properties. The reflexive
controller used here has the following characteristics, which are
different from earlier approaches: (1) Control is mainly local.
Hence, it uses only two signals (AEA=Anterior Extreme Angle and
GC=Ground Contact) which operate at the inter-joint level. All
other signals operate only at single joints. (2) Neither position
control nor trajectory tracking control is used. Instead, the
approximate nature of the local reflexes on each joint allows the
robot mechanics itself (e.g., its passive dynamics) to contribute
substantially to the overall gait trajectory computation. (3) The
motor control scheme used in the local reflexes of our robot is
more straightforward and has more biological plausibility than
that of other robots, because the outputs of the motorneurons in
our reflexive controller are directly driving the motors of the
joints, rather than working as references for position or velocity
control. As a consequence, the neural controller and the robot
mechanics are closely coupled as a neuro-mechanical system and
this study emphasises that dynamically stable biped walking gaits
emerge from the coupling between neural computation and physical
computation. This is demonstrated by different walking
experiments using two real robot as well as by a Poincar\'{e} map
analysis applied on a model of the robot in order to assess its
stability. In addition, this neuronal control structure allows the
use of a policy gradient reinforcement learning algorithm to tune
the parameters of the neurons in real-time, during walking. This
way the robot can reach a record-breaking walking speed of 3.5
leg-lengths per second after only a few minutes of online
learning, which is even comparable to the fastest relative speed
of human walking
A Bio-inspired architecture for adaptive quadruped locomotion over irregular terrain
Tese de doutoramento
Programa Doutoral em Engenharia Electrónica e de ComputadoresThis thesis presents a tentative advancement on walking control of small quadruped and humanoid
position controlled robots, addressing the problem of walk generation by combining dynamical systems
approach to motor control, insights from neuroethology research on vertebrate motor control and
computational neuroscience.
Legged locomotion is a complex dynamical process, despite the seemingly easy and natural behavior
of the constantly present proficiency of legged animals. Research on locomotion and motor control
in vertebrate animals from the last decades has brought to the attention of roboticists, the potential of
the nature’s solutions to robot applications. Recent knowledge on the organization of complex motor
generation and on mechanics and dynamics of locomotion has been successfully exploited to pursue
agile robot locomotion.
The work presented on this manuscript is part of an effort on the pursuit in devising a general,
model free solution, for the generation of robust and adaptable walking behaviors. It strives to devise a
practical solution applicable to real robots, such as the Sony’s quadruped AIBO and Robotis’ DARwIn-
OP humanoid. The discussed solutions are inspired on the functional description of the vertebrate
neural systems, especially on the concept of Central Pattern Generators (CPGs), their structure and
organization, components and sensorimotor interactions. They use a dynamical systems approach for
the implementation of the controller, especially on the use of nonlinear oscillators and exploitation of
their properties.
The main topics of this thesis are divided into three parts.
The first part concerns quadruped locomotion, extending a previous CPG solution using nonlinear
oscillators, and discussing an organization on three hierarchical levels of abstraction, sharing the purpose
and knowledge of other works. It proposes a CPG solution which generates the walking motion
for the whole-leg, which is then organized in a network for the production of quadrupedal gaits. The
devised solution is able to produce goal-oriented locomotion and navigation as directed through highlevel
commands from local planning methods. In this part, active balance on a standing quadruped is
also addressed, proposing a method based on dynamical systems approach, exploring the integration of
parallel postural mechanisms from several sensory modalities. The solutions are all successfully tested on the quadruped AIBO robot.
In the second part, is addressed bipedal walking for humanoid robots. A CPG solution for biped
walking based on the concept of motion primitives is proposed, loosely based on the idea of synergistic
organization of vertebrate motor control. A set of motion primitives is shown to produce the basis
of simple biped walking, and generalizable to goal-oriented walking. Using the proposed CPG, the
inclusion of feedback mechanisms is investigated, for modulation and adaptation of walking, through
phase transition control according to foot load information. The proposed solution is validated on the
humanoid DARwIn-OP, and its application is evaluated within a whole-body control framework.
The third part sidesteps a little from the other two topics. It discusses the CPG as having an alternative
role to direct motor generation in locomotion, serving instead as a processor of sensory information
for a feedback based motor generation. In this work a reflex based walking controller is devised for the
compliant quadruped Oncilla robot, to serve as purely feedback based walking generation. The capabilities
of the reflex network are shown in simulations, followed by a brief discussion on its limitations,
and how they could be improved by the inclusion of a CPG.Esta tese apresenta uma tentativa de avanço no controlo de locomoção para pequenos robôs quadrúpedes
e bipedes controlados por posição, endereçando o problema de geração motora através da combinação
da abordagem de sistemas dinâmicos para o controlo motor, e perspectivas de investigação
neuroetologia no controlo motor vertebrado e neurociência computacional.
Andar é um processo dinâmico e complexo, apesar de parecer um comportamento fácil e natural
devido à presença constante de animais proficientes em locomoção terrestre. Investigação na área da locomoção
e controlo motor em animais vertebrados nas últimas decadas, trouxe à atenção dos roboticistas
o potencial das soluções encontradas pela natureza aplicadas a aplicações robóticas. Conhecimento
recente relativo à geração de comportamentos motores complexos e da mecânica da locomoção tem
sido explorada com sucesso na procura de locomoção ágil na robótica.
O trabalho apresentado neste documento é parte de um esforço no desenho de uma solução geral,
e independente de modelos, para a geração robusta e adaptável de comportamentos locomotores. O
foco é desenhar uma solução prática, aplicável a robôs reais, tal como o quadrúpede Sony AIBO e
o humanóide DARwIn-OP. As soluções discutidas são inspiradas na descrição funcional do sistema
nervoso vertebrado, especialmente no conceito de Central Pattern Generators (CPGs), a sua estrutura e
organização, componentes e interacção sensorimotora. Estas soluções são implementadas usando uma
abordagem em sistemas dinâmicos, focandos o uso de osciladores não lineares e a explorando as suas
propriedades.
Os tópicos principais desta tese estão divididos em três partes.
A primeira parte explora o tema de locomoção quadrúpede, expandindo soluções prévias de CPGs
usando osciladores não lineares, e discutindo uma organização em três níveis de abstracção, partilhando
as ideias de outros trabalhos. Propõe uma solução de CPG que gera os movimentos locomotores
para uma perna, que é depois organizado numa rede, para a produção de marcha quadrúpede. A
solução concebida é capaz de produzir locomoção e navegação, comandada através de comandos de alto
nível, produzidos por métodos de planeamento local. Nesta parte também endereçado o problema da
manutenção do equilíbrio num robô quadrúpede parado, propondo um método baseado na abordagem
em sistemas dinâmicos, explorando a integração de mecanismos posturais em paralelo, provenientes de várias modalidades sensoriais. As soluções são todas testadas com sucesso no robô quadrupede AIBO.
Na segunda parte é endereçado o problema de locomoção bípede. É proposto um CPG baseado
no conceito de motion primitives, baseadas na ideia de uma organização sinergética do controlo motor
vertebrado. Um conjunto de motion primitives é usado para produzir a base de uma locomoção bípede
simples e generalizável para navegação. Esta proposta de CPG é usada para de seguida se investigar
a inclusão de mecanismos de feedback para modulação e adaptação da marcha, através do controlo de
transições entre fases, de acordo com a informação de carga dos pés. A solução proposta é validada
no robô humanóide DARwIn-OP, e a sua aplicação no contexto do framework de whole-body control é
também avaliada.
A terceira parte desvia um pouco dos outros dois tópicos. Discute o CPG como tendo um papel
alternativo ao controlo motor directo, servindo em vez como um processador de informação sensorial
para um mecanismo de locomoção puramente em feedback. Neste trabalho é desenhado um controlador
baseado em reflexos para a geração da marcha de um quadrúpede compliant. As suas capacidades são
demonstradas em simulação, seguidas por uma breve discussão nas suas limitações, e como estas podem
ser ultrapassadas pela inclusão de um CPG.The presented work was possible thanks to the support by the Portuguese Science and Technology Foundation through the PhD grant SFRH/BD/62047/2009
Biologically inspired locomotion control of bipedal robot
Master'sMASTER OF ENGINEERIN
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
Quadruped locomotion reference synthesis wıth central pattern generators tuned by evolutionary algorithms
With the recent advances in sensing, actuating and communication tecnologies and in theory for control and navigation; mobile robotic platforms are seen more promising than ever. This is so for many fields ranging from search and rescue in earthquake sites to military applications. Autonomous or teleoperated land vehicles make a major class of these mobile platforms. Legged robots, with their potential virtues in obstacle avoidance and cross-country capabilities stand out for applications on rugged terrain. In the nature, there are a lot of examples where four-legged anatomy embraces both speed and climbing characteristics. This thesis is on the locomotion reference generation of quadruped robots. Reference generation plays a vital role for the success of the locomotion controller. It involves the timing of the steps and the selection of various spatial parameters. The generated references should be suitable to be followed. They should not be over-demanding to cause the robot fall by loosing its balance. Nature tells that the pattern of the steps, that is, the gait, also changes with the speed of locomotion. A well-planned reference generation algorithm should take gait transitions into account. Central Pattern Generators (CPG) are biologically-inspired tools for legged-robot locomotion reference generation. They represent one of the main stream quadruped robot locomotion synthesis approaches, along with Zero Moment Point (ZMP) based techniques and trial–and–error methods. CPGs stand out with their natural convenience for gait transitions. This is so because of the stable limit cycle behavior inhertent in their structure. However, the parameter selection and tuning of this type of reference generators is difficult. Often, trial–and–error iterations are employed to obtain suitable parameters. The background of complicated dynamics and difficulties in reference generation makes automatic tuning of CPGs an interesting area of research. A natural command for a legged robot is the speed of its locomotion. When considered from kinematics point of view, there is no unique set of walking parameters which yield a given desired speed. However, some of the solutions can be more suitable for a stable walk, whereas others may lead to instability and cause robot to fall. This thesis proposes a quadruped gait tuning method based on evolutionary methods. A velocity command is given as the input to the system. A CPG based reference generation method is employed. 3D full-dynamics locomotion simulations with a 16-degrees-of-freedom (DOF) quadruped robot model are performed to assess the fitness of artificial populations. The fitness is measured by three different cost functions. The first cost function measures the amount of support the simulated quadruped receives from torsional virtual springs and dampers opposing the changes in body orientation, whereas the second one is a measure of energy efficiency in the locomotion. The third cost function is a combination of the firs two. Tuning results with the three cost functions are obtained and compared. Cross-over and mutation mechanisms generate new populations. Simulation results verify the merits of the proposed reference generation and tuning method
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