13,501 research outputs found
Paraplegic standing supported by FES-controlled ankle stiffness
The objective of this paper was to investigate whether a paraplegic subject-is able to maintain balance during standing by means of voluntary and reflex activity of the upper body while being supported by closed loop controlled ankle stiffness using FES. The knees and hips of the subject were held in extended positions by a mechanical apparatus, which restricted movement to the sagittal plane. The subject underwent several training sessions where the appropriate level of stiffness around the ankles was maintained by the mechanical apparatus. This enabled the subject to learn how to use the upper body for. balancing. After the subject gained adequate skills closed-loop FES was employed to regulate ankle stiffness, replacing the stiffness provided by the apparatus. A method to control antagonist muscle moment was implemented. In subsequent standing sessions, the subject had no difficulties in maintaining balance. When the FES, support was withheld, the ability to balance was lost
Straight-Leg Walking Through Underconstrained Whole-Body Control
We present an approach for achieving a natural, efficient gait on bipedal
robots using straightened legs and toe-off. Our algorithm avoids complex height
planning by allowing a whole-body controller to determine the straightest
possible leg configuration at run-time. The controller solutions are biased
towards a straight leg configuration by projecting leg joint angle objectives
into the null-space of the other quadratic program motion objectives. To allow
the legs to remain straight throughout the gait, toe-off was utilized to
increase the kinematic reachability of the legs. The toe-off motion is achieved
through underconstraining the foot position, allowing it to emerge naturally.
We applied this approach of under-specifying the motion objectives to the Atlas
humanoid, allowing it to walk over a variety of terrain. We present both
experimental and simulation results and discuss performance limitations and
potential improvements.Comment: Submitted to 2018 IEEE International Conference on Robotics and
Automatio
Stationary Cycling Induced by Switched Functional Electrical Stimulation Control
Functional electrical stimulation (FES) is used to activate the dysfunctional
lower limb muscles of individuals with neuromuscular disorders to produce
cycling as a means of exercise and rehabilitation. However, FES-cycling is
still metabolically inefficient and yields low power output at the cycle crank
compared to able-bodied cycling. Previous literature suggests that these
problems are symptomatic of poor muscle control and non-physiological muscle
fiber recruitment. The latter is a known problem with FES in general, and the
former motivates investigation of better control methods for FES-cycling.In
this paper, a stimulation pattern for quadriceps femoris-only FES-cycling is
derived based on the effectiveness of knee joint torque in producing forward
pedaling. In addition, a switched sliding-mode controller is designed for the
uncertain, nonlinear cycle-rider system with autonomous state-dependent
switching. The switched controller yields ultimately bounded tracking of a
desired trajectory in the presence of an unknown, time-varying, bounded
disturbance, provided a reverse dwell-time condition is satisfied by
appropriate choice of the control gains and a sufficient desired cadence.
Stability is derived through Lyapunov methods for switched systems, and
experimental results demonstrate the performance of the switched control system
under typical cycling conditions.Comment: 8 pages, 3 figures, submitted to ACC 201
Online identification and nonlinear control of the electrically stimulated quadriceps muscle
A new approach for estimating nonlinear models of the electrically stimulated quadriceps muscle group under nonisometric conditions is investigated. The model can be used for designing controlled neuro-prostheses. In order to identify the muscle dynamics (stimulation pulsewidth-active knee moment relation) from discrete-time angle measurements only, a hybrid model structure is postulated for the shank-quadriceps dynamics. The model consists of a relatively well known time-invariant passive component and an uncertain time-variant active component. Rigid body dynamics, described by the Equation of Motion (EoM), and passive joint properties form the time-invariant part. The actuator, i.e. the electrically stimulated muscle group, represents the uncertain time-varying section. A recursive algorithm is outlined for identifying online the stimulated quadriceps muscle group. The algorithm requires EoM and passive joint characteristics to be known a priori. The muscle dynamics represent the product of a continuous-time nonlinear activation dynamics and a nonlinear static contraction function described by a Normalised Radial Basis Function (NRBF) network which has knee-joint angle and angular velocity as input arguments. An Extended Kalman Filter (EKF) approach is chosen to estimate muscle dynamics parameters and to obtain full state estimates of the shank-quadriceps dynamics simultaneously. The latter is important for implementing state feedback controllers. A nonlinear state feedback controller using the backstepping method is explicitly designed whereas the model was identified a priori using the developed identification procedure
On Advanced Mobility Concepts for Intelligent Planetary Surface Exploration
Surface exploration by wheeled rovers on Earth's Moon (the two Lunokhods) and Mars (Nasa's Sojourner and the two MERs) have been followed since many years already very suc-cessfully, specifically concerning operations over long time. However, despite of this success, the explored surface area was very small, having in mind a total driving distance of about 8 km (Spirit) and 21 km (Opportunity) over 6 years of operation. Moreover, ESA will send its ExoMars rover in 2018 to Mars, and NASA its MSL rover probably this year. However, all these rovers are lacking sufficient on-board intelligence in order to overcome longer dis-tances, driving much faster and deciding autonomously on path planning for the best trajec-tory to follow. In order to increase the scientific output of a rover mission it seems very nec-essary to explore much larger surface areas reliably in much less time. This is the main driver for a robotics institute to combine mechatronics functionalities to develop an intelligent mo-bile wheeled rover with four or six wheels, and having specific kinematics and locomotion suspension depending on the operational terrain of the rover to operate. DLR's Robotics and Mechatronics Center has a long tradition in developing advanced components in the field of light-weight motion actuation, intelligent and soft manipulation and skilled hands and tools, perception and cognition, and in increasing the autonomy of any kind of mechatronic systems. The whole design is supported and is based upon detailed modeling, optimization, and simula-tion tasks. We have developed efficient software tools to simulate the rover driveability per-formance on various terrain characteristics such as soft sandy and hard rocky terrains as well as on inclined planes, where wheel and grouser geometry plays a dominant role. Moreover, rover optimization is performed to support the best engineering intuitions, that will optimize structural and geometric parameters, compare various kinematics suspension concepts, and make use of realistic cost functions like mass and consumed energy minimization, static sta-bility, and more. For self-localization and safe navigation through unknown terrain we make use of fast 3D stereo algorithms that were successfully used e.g. in unmanned air vehicle ap-plications and on terrestrial mobile systems. The advanced rover design approach is applica-ble for lunar as well as Martian surface exploration purposes. A first mobility concept ap-proach for a lunar vehicle will be presented
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