192 research outputs found
Imitating human motion using humanoid upper body models
Includes abstract.Includes bibliographical references.This thesis investigates human motion imitation of five different humanoid upper bodies (comprised of the torso and upper limbs) using human dance motion as a case study. The humanoid models are based on five existing humanoids, namely, ARMAR, HRP-2, SURALP, WABIAN-2, and WE-4RII. These humanoids are chosen for their different structures and range of joint motion
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Design of a Passive Exoskeleton Spine
In this thesis, a passive exoskeleton spine was designed and evaluated by a series of biomechanics simulations. The design objectives were to reduce the human operator’s back muscle efforts and the intervertebral reaction torques during a full range sagittal plane spine flexion/extension. The biomechanics simulations were performed using the OpenSim modeling environment. To manipulate the simulations, a full body musculoskeletal model was created based on the OpenSim gait2354 and “lumbar spine” models. To support flexion and extension of the torso a “push-pull” strategy was proposed by applying external pushing and pulling forces on different locations on the torso. The external forces were optimized via simulations and then a physical exoskeleton prototype was built to evaluate the “push-pull” strategy in vivo. The prototype was tested on three different subjects where the sEMG and inertial data were collected to estimate the muscle force reduction and intervertebral torque reduction. The prototype assisted the users in sagittal plane flexion/extension and reduced the average muscle force and intervertebral reaction torque by an average of 371 N and 29 Nm, respectively
Design, modeling and implementation of a soft robotic neck for humanoid robots
Mención Internacional en el título de doctorSoft humanoid robotics is an emerging field that combines the flexibility and safety of soft
robotics with the form and functionality of humanoid robotics. This thesis explores the potential
for collaboration between these two fields with a focus on the development of soft joints for the
humanoid robot TEO. The aim is to improve the robot’s adaptability and movement, which are
essential for an efficient interaction with its environment.
The research described in this thesis involves the development of a simple and easily transportable
soft robotic neck for the robot, based on a 2 Degree of Freedom (DOF) Cable Driven
Parallel Mechanism (CDPM). For its final integration into TEO, the proposed design is later
refined, resulting in an efficiently scaled prototype able to face significant payloads.
The nonlinear behaviour of the joints, due mainly to the elastic nature of their soft links,
makes their modeling a challenging issue, which is addressed in this thesis from two perspectives:
first, the direct and inverse kinematic models of the soft joints are analytically studied,
based on CDPM mathematical models; second, a data-driven system identification is performed
based on machine learning techniques. Both approaches are deeply studied and compared, both
in simulation and experimentally.
In addition to the soft neck, this thesis also addresses the design and prototyping of a soft
arm capable of handling external loads. The proposed design is also tendon-driven and has a
morphology with two main bending configurations, which provides more versatility compared
to the soft neck.
In summary, this work contributes to the growing field of soft humanoid robotics through
the development of soft joints and their application to the humanoid robot TEO, showcasing the
potential of soft robotics to improve the adaptability, flexibility, and safety of humanoid robots.
The development of these soft joints is a significant achievement and the research presented in this thesis paves the way for further exploration and development in this field.La robótica humanoide blanda es un campo emergente que combina la flexibilidad y seguridad
de la robótica blanda con la forma y funcionalidad de la robótica humanoide. Esta
tesis explora el potencial de colaboración entre estos dos campos centrándose en el desarrollo
de una articulación blanda para el cuello del robot humanoide TEO. El objetivo es mejorar la
adaptabilidad y el movimiento del robot, esenciales para una interacción eficaz con su entorno.
La investigación descrita en esta tesis consiste en el desarrollo de un prototipo sencillo
y fácilmente transportable de cuello blando para el robot, basado en un mecanismo paralelo
actuado por cable de 2 grados de libertad. Para su integración final en TEO, el diseño propuesto
es posteriormente refinado, resultando en un prototipo eficientemente escalado capaz de manejar
cargas significativas.
El comportamiemto no lineal de estas articulaciones, debido fundamentalmente a la naturaleza
elástica de sus eslabones blandos, hacen de su modelado un gran reto, que en esta tesis
se aborda desde dos perspectivas diferentes: primero, los modelos cinemáticos directo e inverso
de las articulaciones blandas se estudian analíticamente, basándose en modelos matemáticos de
mecanismos paralelos actuados por cable; segundo, se aborda el problema de la identificación
del sistema mediante técnicas basadas en machine learning. Ambas propuestas se estudian y
comparan en profundidad, tanto en simulación como experimentalmente.
Además del cuello blando, esta tesis también aborda el diseño de un brazo robótico blando
capaz de manejar cargas externas. El diseño propuesto está igualmente basado en accionamiento
por tendones y tiene una morfología con dos configuraciones principales de flexión, lo que
proporciona una mayor versatilidad en comparación con el cuello robótico blando.
En resumen, este trabajo contribuye al creciente campo de la robótica humanoide blanda
mediante el desarrollo de articulaciones blandas y su aplicación al robot humanoide TEO, mostrando el potencial de la robótica blanda para mejorar la adaptabilidad, flexibilidad y seguridad
de los robots humanoides. El desarrollo de estas articulaciones es una contribución
significativa y la investigación presentada en esta tesis allana el camino hacia nuevos desarrollos
y retos en este campo.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidenta: Cecilia Elisabet García Cena.- Secretario: Dorin Sabin Copaci.- Vocal: Martin Fodstad Stole
Kinematic Modelling and Motion Analysis of a Humanoid Torso Mechanism
This paper introduces a novel kinematic model for a tendon-driven compliant torso mechanism for humanoid robots, which describes the complex behaviour of a system characterised by the interaction of a complex compliant element with rigid bodies and actuation tendons. Inspired by a human spine, the proposed mechanism is based on a flexible backbone whose shape is controlled by two pairs of antagonistic tendons. First, the structure is analysed to identify the main modes of motion. Then, a constant curvature kinematic model is extended to describe the behaviour of the torso mechanism under examination, which includes axial elongation/compression and torsion in addition to the main bending motion. A linearised stiffness model is also formulated to estimate the static response of the backbone. The novel model is used to evaluate the workspace of an example mechanical design, and then it is mapped onto a controller to validate the results with an experimental test on a prototype. By replacing a previous approximated model calibrated on experimental data, this kinematic model improves the accuracy and efficiency of the torso mechanism and enables the performance evaluation of the robot over the reachable workspace, to ensure that the tendon-driven architecture operates within its wrench-closure workspace
The design, analysis and evaluation of a humanoid robotic head
Where robots interact directly with humans on a ‘one-to-one’ basis, it is often quite important for them to be emotionally acceptable, hence the growing interesting in humanoid robots. In some applications it is important that these robots do not just resemble a human being in appearance, but also move like a human being too, to make them emotionally acceptable – hence the interest in biomimetic humanoid robotics. The research described in this thesis is concerned with the design, analysis and evaluation of a biomimetic humanoid robotic head. It is biomimetic in terms of physical design - which is based around a simulated cervical spine, and actuation, which is achieved using pneumatic air muscles (PAMS). The primary purpose of the research, however, and the main original contribution, was to create a humanoid robotic head capable of mimicking complex non-purely rotational human head movements. These include a sliding front-to-back, lateral movement, and a sliding, side-to-side lateral movement. A number of different approaches were considered and evaluated, before finalising the design.
As there are no generally accepted metrics in the literature regarding the full range of human head movements, the best benchmarks for comparison are the angular ranges and speeds of humans in terms on pitch (nod), roll (tilt) and yaw (rotate) were used for comparison, and these they were considered desired ranges for the robot. These measured up well in comparison in terms of angular speed and some aspects of range of human necks. Additionally, the lateral movements were measured during the nod, tilt and rotate movements, and established the ability of the robot to perform the complex lateral movements seen in humans, thus proving the benefits of the cervical spine approach.
Finally, the emotional acceptance of the robot movements was evaluated against another (commercially made) robot and a human. This was a blind test, in that the (human) evaluators had no way of knowing whether they were evaluation a human or a robot. The tests demonstrated that on scales of Fake/Natural, Machinelike/Humanlike and Unconcsious/Conscious the robot the robot scored similarly to the human
Anticipatory models of human movements and dynamics: the roadmap of the AnDy project
International audienceFuture robots will need more and more anticipation capabilities, to properly react to human actions and provide efficient collaboration. To achieve this goal, we need new technologies that not only estimate the motion of the humans, but that fully describe the whole-body dynamics of the interaction and that can also predict its outcome. These hardware and software technologies are the goal of the European project AnDy. In this paper, we describe the roadmap of AnDy, which leverages existing technologies to endow robots with the ability to control physical collaboration through intentional interaction. To achieve this goal, AnDy relies on three technological and scientific breakthroughs. First, AnDy will innovate the way of measuring human whole-body motions by developing the wearable AnDySuit, which tracks motions and records forces. Second, AnDy will develop the AnDyModel, which combines ergonomic models with cognitive predictive models of human dynamic behavior in collaborative tasks, learned from data acquired with the AnDySuit. Third, AnDy will propose AnDyControl, an innovative technology for assisting humans through pre-dictive physical control, based on AnDyModel. By measuring and modeling human whole-body dynamics, AnDy will provide robots with a new level of awareness about human intentions and ergonomy. By incorporating this awareness on-line in the robot's controllers, AnDy paves the way for novel applications of physical human-robot collaboration in manufacturing, health-care, and assisted living
Development and Characteristics of a Highly Biomimetic Robotic Shoulder Through Bionics-Inspired Optimization
This paper critically analyzes conventional and biomimetic robotic arms,
underscoring the trade-offs between size, motion range, and load capacity in
current biomimetic models. By delving into the human shoulder's mechanical
intelligence, particularly the glenohumeral joint's intricate features such as
its unique ball-and-socket structure and self-locking mechanism, we pinpoint
innovations that bolster both stability and mobility while maintaining
compactness. To substantiate these insights, we present a groundbreaking
biomimetic robotic glenohumeral joint that authentically mirrors human
musculoskeletal elements, from ligaments to tendons, integrating the biological
joint's mechanical intelligence. Our exhaustive simulations and tests reveal
enhanced flexibility and load capacity for the robotic joint. The advanced
robotic arm demonstrates notable capabilities, including a significant range of
motions and a 4 kg payload capacity, even exerting over 1.5 Nm torque. This
study not only confirms the human shoulder joint's mechanical innovations but
also introduces a pioneering design for a next-generation biomimetic robotic
arm, setting a new benchmark in robotic technology
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