4,164 research outputs found
Comfort-Centered Design of a Lightweight and Backdrivable Knee Exoskeleton
This paper presents design principles for comfort-centered wearable robots
and their application in a lightweight and backdrivable knee exoskeleton. The
mitigation of discomfort is treated as mechanical design and control issues and
three solutions are proposed in this paper: 1) a new wearable structure
optimizes the strap attachment configuration and suit layout to ameliorate
excessive shear forces of conventional wearable structure design; 2) rolling
knee joint and double-hinge mechanisms reduce the misalignment in the sagittal
and frontal plane, without increasing the mechanical complexity and inertia,
respectively; 3) a low impedance mechanical transmission reduces the reflected
inertia and damping of the actuator to human, thus the exoskeleton is
highly-backdrivable. Kinematic simulations demonstrate that misalignment
between the robot joint and knee joint can be reduced by 74% at maximum knee
flexion. In experiments, the exoskeleton in the unpowered mode exhibits 1.03 Nm
root mean square (RMS) low resistive torque. The torque control experiments
demonstrate 0.31 Nm RMS torque tracking error in three human subjects.Comment: 8 pages, 16figures, Journa
Finite Time Robust Control of the Sit-to-Stand Movement for Powered Lower Limb Orthoses
This study presents a technique to safely control the Sit-to-Stand movement
of powered lower limb orthoses in the presence of parameter uncertainty. The
weight matrices used to calculate the finite time horizon linear-quadratic
regulator (LQR) gain in the feedback loop are chosen from a pool of candidates
as to minimize a robust performance metric involving induced gains that measure
the deviation of variables of interest in a linear time-varying (LTV) system,
at specific times within a finite horizon, caused by a perturbation signal
modeling the variation of the parameters. Two relevant Sit-to-Stand movements
are simulated for drawing comparisons with the results documented in a previous
work.Comment: 8 pages, 14 figures, ACC 2018 Submissio
Human-robot interaction for assistive robotics
This dissertation presents an in-depth study of human-robot interaction (HRI) withapplication to assistive robotics. In various studies, dexterous in-hand manipulation is included, assistive robots for Sit-To-stand (STS) assistance along with the human intention estimation. In Chapter 1, the background and issues of HRI are explicitly discussed. In Chapter 2, the literature review introduces the recent state-of-the-art research on HRI, such as physical Human-Robot Interaction (HRI), robot STS assistance, dexterous in hand manipulation and human intention estimation. In Chapter 3, various models and control algorithms are described in detail. Chapter 4 introduces the research equipment. Chapter 5 presents innovative theories and implementations of HRI in assistive robotics, including a general methodology of robotic assistance from the human perspective, novel hardware design, robotic sit-to-stand (STS) assistance, human intention estimation, and control
Human sit-to-stand transfer modeling towards intuitive and biologically-inspired robot assistance
© 2016, Springer Science+Business Media New York. Sit-to-stand (STS) transfers are a common human task which involves complex sensorimotor processes to control the highly nonlinear musculoskeletal system. In this paper, typical unassisted and assisted human STS transfers are formulated as optimal feedback control problem that finds a compromise between task end-point accuracy, human balance, energy consumption, smoothness of motion and control and takes further human biomechanical control constraints into account. Differential dynamic programming is employed, which allows taking the full, nonlinear human dynamics into consideration. The biomechanical dynamics of the human is modeled by a six link rigid body including leg, trunk and arm segments. Accuracy of the proposed modelling approach is evaluated for different human healthy and patient/elderly subjects by comparing simulations and experimentally collected data. Acceptable model accuracy is achieved with a generic set of constant weights that prioritize the different criteria. Finally, the proposed STS model is used to determine optimal assistive strategies suitable for either a person with specific body segment weakness or a more general weakness. These strategies are implemented on a robotic mobility assistant and are intensively evaluated by 33 elderlies, mostly not able to perform unassisted STS transfers. The validation results show a promising STS transfer success rate and overall user satisfaction
RGBD Datasets: Past, Present and Future
Since the launch of the Microsoft Kinect, scores of RGBD datasets have been
released. These have propelled advances in areas from reconstruction to gesture
recognition. In this paper we explore the field, reviewing datasets across
eight categories: semantics, object pose estimation, camera tracking, scene
reconstruction, object tracking, human actions, faces and identification. By
extracting relevant information in each category we help researchers to find
appropriate data for their needs, and we consider which datasets have succeeded
in driving computer vision forward and why.
Finally, we examine the future of RGBD datasets. We identify key areas which
are currently underexplored, and suggest that future directions may include
synthetic data and dense reconstructions of static and dynamic scenes.Comment: 8 pages excluding references (CVPR style
Learning Agile Bipedal Motions on a Quadrupedal Robot
Can a quadrupedal robot perform bipedal motions like humans? Although
developing human-like behaviors is more often studied on costly bipedal robot
platforms, we present a solution over a lightweight quadrupedal robot that
unlocks the agility of the quadruped in an upright standing pose and is capable
of a variety of human-like motions. Our framework is with a bi-level structure.
At the low level is a motion-conditioned control policy that allows the
quadrupedal robot to track desired base and front limb movements while
balancing on two hind feet. The policy is commanded by a high-level motion
generator that gives trajectories of parameterized human-like motions to the
robot from multiple modalities of human input. We for the first time
demonstrate various bipedal motions on a quadrupedal robot, and showcase
interesting human-robot interaction modes including mimicking human videos,
following natural language instructions, and physical interaction
Enabling Human-Robot Collaboration via Holistic Human Perception and Partner-Aware Control
As robotic technology advances, the barriers to the coexistence of humans and robots are slowly coming down. Application domains like elderly care, collaborative manufacturing, collaborative manipulation, etc., are considered the need of the hour, and progress in robotics holds the potential to address many societal challenges. The future socio-technical systems constitute of blended workforce with a symbiotic relationship between human and robot partners working collaboratively. This thesis attempts to address some of the research challenges in enabling human-robot collaboration. In particular, the challenge of a holistic perception of a human partner to continuously communicate his intentions and needs in real-time to a robot partner is crucial for the successful realization of a collaborative task. Towards that end, we present a holistic human perception framework for real-time monitoring of whole-body human motion and dynamics. On the other hand, the challenge of leveraging assistance from a human partner will lead to improved human-robot collaboration. In this direction, we attempt at methodically defining what constitutes assistance from a human partner and propose partner-aware robot control strategies to endow robots with the capacity to meaningfully engage in a collaborative task
Design of an Elastic Actuation System for a Gait-Assistive Active Orthosis for Incomplete Spinal Cord Injured Subjects
A spinal cord injury severely reduces the quality of life of affected people. Following the injury,
limitations of the ability to move may occur due to the disruption of the motor and sensory functions
of the nervous system depending on the severity of the lesion. An active stance-control
knee-ankle-foot orthosis was developed and tested in earlier works to aid incomplete SCI subjects
by increasing their mobility and independence. This thesis aims at the incorporation of
elastic actuation into the active orthosis to utilise advantages of the compliant system regarding
efficiency and human-robot interaction as well as the reproduction of the phyisological compliance
of the human joints. Therefore, a model-based procedure is adapted to the design of
an elastic actuation system for a gait-assisitve active orthosis. A determination of the optimal
structure and parameters is undertaken via optimisation of models representing compliant actuators
with increasing level of detail. The minimisation of the energy calculated from the positive
amount of power or from the absolute power of the actuator generating one human-like gait cycle
yields an optimal series stiffness, which is similar to the physiological stiffness of the human
knee during the stance phase. Including efficiency factors for components, especially the consideration
of the electric model of an electric motor yields additional information. A human-like
gait cycle contains high torque and low velocities in the stance phase and lower torque combined
with high velocities during the swing. Hence, the efficiency of an electric motor with a gear unit
is only high in one of the phases. This yields a conceptual design of a series elastic actuator with
locking of the actuator position during the stance phase. The locked position combined with the
series compliance allows a reproduction of the characteristics of the human gait cycle during
the stance phase. Unlocking the actuator position for the swing phase enables the selection of
an optimal gear ratio to maximise the recuperable energy. To evaluate the developed concept,
a laboratory specimen based on an electric motor, a harmonic drive gearbox, a torsional series
spring and an electromagnetic brake is designed and appropriate components are selected. A
control strategy, based on impedance control, is investigated and extended with a finite state
machine to activate the locking mechanism. The control scheme and the laboratory specimen
are implemented at a test bench, modelling the foot and shank as a pendulum articulated at the
knee. An identification of parameters yields high and nonlinear friction as a problem of the system,
which reduces the energy efficiency of the system and requires appropriate compensation.
A comparison between direct and elastic actuation shows similar results for both systems at the
test bench, showing that the increased complexity due to the second degree of freedom and
the elastic behaviour of the actuator is treated properly. The final proof of concept requires the
implementation at the active orthosis to emulate uncertainties and variations occurring during
the human gait
Task Feasibility Maximization using Model-Free Policy Search and Model-Based Whole-Body Control
Producing feasible motions for highly redundant robots, such as humanoids, is a complicated and high-dimensional problem.Model-based whole-body control of such robots, can generate complex dynamic behaviors through the simultaneous execution of multiple tasks.Unfortunately, tasks are generally planned without close consideration for the underlying controller being used, or the other tasks being executed, and are often infeasible when executed on the robot. Consequently, there is no guarantee that the motion will be accomplished.In this work, we develop an optimization loop which automatically improves task feasibility using model-free policy search in conjunction with model-based whole-body control.This combination allows problems to be solved, which would be otherwise intractable using simply one or the other.Through experiments on both the simulated and real iCub humanoid robot, we show that by optimizing task feasibility, initially infeasible complex dynamic motions can be realized --- specifically, a sit-to-stand transition
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