Lower-limb assisted exoskeletons are widely researched for movement assistance or rehabilitation training. Due to advantages of compliance with human body and lightweight, some cable-driven prototypes have been developed, but most of these can assist only unidirectional movement. In this paper we present an untethered cable-driven ankle exoskeleton that can achieve plantarflexion-dorsiflexion bidirectional motion bilaterally using a pair of single motors. The main weights of the exoskeleton, i.e., the motors, power supplement units, and control units, were placed close to the proximity of the human body, i.e., the waist, to reduce the redundant rotation inertia which would apply on the wearer’s leg. A cable force transmission system based on gear-pulley assemblies was designed to transfer the power from the motor to the end-effector effectively. A cable self-tension device on the power output unit was designed to tension the cable during walking. The gait detection system based on a foot pressure sensor and an inertial measurement unit (IMU) could identify the gait cycle and gait states efficiently. To validate the power output performance of the exoskeleton, a torque tracking experiment was conducted. When the subject was wearing the exoskeleton with power on, the muscle activity of the soleus was reduced by 5.2% compared to the state without wearing the exoskeleton. This preliminarily verifies the positive assistance effect of our exoskeleton. The study in this paper demonstrates the promising application of a lightweight cable-driven exoskeleton on human motion augmentation or rehabilitation.

Lower-limb exoskeletons are of great interest in the robotics community because of their various applications in enhancement and rehabilitation. In this paper we present an autonomous exoskeleton platform for ankle plantarflexion assistance. The untethered exoskeleton has a high efficiency transmission system with reduction ratio of 27.4:1. This allows relocating the actuator to the wearer's hip, which reduces device inertia. A feed-forward controller based on field oriented control was implemented to control the brushless DC motor on the exoskeleton. Through various performance tests, the exoskeleton was shown to provide a torque control bandwidth of 17.5Hz and can effectively track biological torque profiles. The augmentation factor (AF) of the exoskeleton is 64.7W, implying potential to reduce walking metabolic cost. This exoskeleton establishes an autonomous platform for experiments involving ankle assistance.

Humans employ a high degree of redundancy in joint actuation, with different combinations of muscle and tendon action providing the same net joint torque. Both the resolution of these redundancies and the energetics of such systems depend on the dynamic properties of muscles and tendons, particularly their force-length relations. Current walking models that use stock parameters when simulating muscle-tendon dynamics tend to significantly overestimate metabolic consumption, perhaps because they do not adequately consider the role of elasticity. As an alternative, we posit that the muscle-tendon morphology of the human leg has evolved to maximize the metabolic efficiency of walking at self-selected speed. We use a data-driven approach to evaluate this hypothesis, utilizing kinematic, kinetic, electromyographic (EMG), and metabolic data taken from five participants walking at self-selected speed. The kinematic and kinetic data are used to estimate muscle-tendon lengths, muscle moment arms, and joint moments while the EMG data are used to estimate muscle activations. For each subject we perform an optimization using prescribed skeletal kinematics, varying the parameters that govern the force-length curve of each tendon as well as the strength and optimal fiber length of each muscle while seeking to simultaneously minimize metabolic cost and maximize agreement with the estimated joint moments. We find that the metabolic cost of transport (MCOT) values of our participants may be correctly matched (on average 0.36±0.02 predicted, 0.35±0.02 measured) with acceptable joint torque fidelity through application of a single constraint to the muscle metabolic budget. The associated optimal muscle-tendon parameter sets allow us to estimate the forces and states of individual muscles, resolving redundancies in joint actuation and lending insight into the potential roles and control objectives of the muscles of the leg throughout the gait cycle.

A common feature in biological neuromuscular systems is the redundancy in joint actuation. Understanding how these redundancies are resolved in typical joint movements has been a long-standing problem in biomechanics, neuroscience and prosthetics. Many empirical studies have uncovered neural, mechanical and energetic aspects of how humans resolve these degrees of freedom to actuate leg joints for common tasks like walking. However, a unifying theoretical framework that explains the many independent empirical observations and predicts individual muscle and tendon contributions to joint actuation is yet to be established. Here we develop a computational framework to address how the ankle joint actuation problem is resolved by the neuromuscular system in walking. Our framework is founded upon the proposal that a consideration of both neural control and leg muscle-tendon morphology is critical to obtain predictive, mechanistic insight into individual muscle and tendon contributions to joint actuation. We examine kinetic, kinematic and electromyographic data from healthy walking subjects to find that human leg muscle-tendon morphology and neural activations enable a metabolically optimal realization of biological ankle mechanics in walking. This optimal realization (a) corresponds to independent empirical observations of operation and performance of the soleus and gastrocnemius muscles, (b) gives rise to an efficient load-sharing amongst ankle muscle-tendon units and (c) causes soleus and gastrocnemius muscle fibers to take on distinct mechanical roles of force generation and power production at the end of stance phase in walking. The framework outlined here suggests that the dynamical interplay between leg structure and neural control may be key to the high walking economy of humans, and has implications as a means to obtain insight into empirically inaccessible features of individual muscle and tendons in biomechanical tasks.

Integrative approaches to studying the coupled dynamics of skeletal muscles with their loads while under neural control have focused largely on questions pertaining to the postural and dynamical stability of animals and humans. Prior studies have focused on how the central nervous system actively modulates muscle mechanical impedance to generate and stabilize motion and posture. However, the question of whether muscle impedance properties can be neurally modulated to create favorable mechanical energetics, particularly in the context of periodic tasks, remains open. Through muscle stiffness tuning, we hypothesize that a pair of antagonist muscles acting against a common load may produce significantly more power synergistically than individually when impedance matching conditions are met between muscle and load. Since neurally modulated muscle stiffness contributes to the coupled muscle-load stiffness, we further anticipate that power-optimal oscillation frequencies will occur at frequencies greater than the natural frequency of the load. These hypotheses were evaluated computationally by applying optimal control methods to a bilinear muscle model, and also evaluated through in vitro measurements on frog Plantaris longus muscles acting individually and in pairs upon a mass-spring-damper load. We find a 7-fold increase in mechanical power when antagonist muscles act synergistically compared to individually at a frequency higher than the load natural frequency. These observed behaviors are interpreted in the context of resonance tuning and the engineering notion of impedance matching. These findings suggest that the central nervous system can adopt strategies to harness inherent muscle impedance in relation to external loads to attain favorable mechanical energetics.

In this paper, we study the mechanical behavior of leg muscles and tendons during human walking in order to motivate the design of economical robotic legs. We hypothesize that quasi-passive, series-elastic clutch units spanning the knee joint in a musculoskeletal arrangement can capture the dominant mechanical behaviors of the human knee in level-ground walking. Since the mechanical work done by the knee joint throughout a level-ground self-selected-speed walking cycle is negative, and since there is no element capable of dissipating mechanical energy in the musculoskeletal model, biarticular elements would necessarily need to transfer energy from the knee joint to hip and/or ankle joints. This mechanism would reduce the necessary actuator work and improve the mechanical economy of a human-like walking robot. As a preliminary evaluation of these hypotheses, we vary model parameters, or spring constants and clutch engagement times, using an optimization scheme that minimizes ankle and hip actuator positive work while still maintaining human-like knee mechanics. For model evaluation, kinetic and kinematic gait data were employed from one study participant walking across a level-ground surface at a self-selected gait speed. With this under-actuated leg model, we find good agreement between the model's quasi-passive knee torque and experimental knee values, suggesting that a knee actuator is not necessary for level-ground robotic ambulation at self-selected gait speeds.

Recent humanoid control investigations have emphasized the importance of controlling whole-body angular momentum throughout a movement task. For typical movement tasks, such as normal walking, such controllers minimize fluctuations in angular momentum about the center of mass (CM). This minimization is consistent with observed behavior of humans for such tasks. However, there are cases where such minimization is not desirable. In this study, we investigate movement tasks where bipedal balance control requires a relaxation of the goal of minimizing whole-body angular moment. We construct a humanoid model having a human-like mass distribution, and a Moment-Exploiting Control algorithm that modulates whole-body angular momentum to enhance CM control. The model only requires reference trajectories for CM position and torso orientation. Joint reference trajectories are not required. While balancing on one leg, we show that the controller is capable of correcting errors in CM state by sacrificing angular postural goals for the swing leg, trunk and head. This prioritization capability provides robustness to significant disturbances, without the need to plan new reference trajectories. We compare the dynamic behavior of our humanoid model to that of human test participants. While standing on one leg, the model, like the human, is shown to reposition its CM just above the stance foot from an initial body state where CM velocity is zero, and the ground CM projection falls outside the foot envelope.

In this paper, we present an under-actuated model of human walking, comprising only a soleus muscle and flexion/extension monoarticular hip muscles. The remaining muscle groups of the human leg are modeled using quasi-passive, series-elastic clutch elements. We hypothesize that series-elastic clutch units spanning the knee joint in a musculoskeletal arrangement can capture the dominant mechanical behaviors of the human knee in level-ground walking. As an evaluation of the musculoskeletal model, we vary model parameters, or spring constants, and muscle control parameters using an optimization scheme that maximizes walking distance and minimizes the mechanical economy of walking. We used a positive force feedback reflex control for the model's soleus muscle, and upper body position control for the hip muscles. The model's clutches were engaged/disengaged using simple state machine controllers. For model evaluation, a forward dynamics simulation was conducted, and the resulting mechanics were compared to human walking data. The model makes qualitative predictions of joint mechanics, electromyography and mechanical economy.

At moderate to fast walking speeds, the human ankle provides net positive work at high-mechanical-power output to propel the body upward and forward during the stance period. On the contrary, conventional ankle-foot prostheses exhibit a passive-elastic response during stance, and consequently, cannot provide net work. Clinical studies indicate that transtibial amputees using conventional prostheses have higher gait metabolic rates than normal. Researchers believe that the main cause for these higher rates is due to the inability of conventional prostheses to provide sufficient positive power at terminal stance in the trailing leg to limit heel strike losses of the adjacent leading leg. In this investigation, we evaluate the hypothesis that a powered ankle-foot prosthesis, capable of providing human-like ankle work and power during stance, can decrease the metabolic cost of transport (COT) compared to a conventional passive-elastic prosthesis. To test the hypothesis, a powered prosthesis is built that comprises a unidirectional spring, configured in parallel with a force-controllable actuator with series elasticity. The prosthesis is shown to deliver the high mechanical power and net positive work observed in normal human walking. The rate of oxygen consumption and carbon dioxide production is measured as a determinant of metabolic rate on three unilateral transtibial amputees walking at self-selected speeds. We find that the powered prosthesis decreases the amputee's metabolic COT on average by 14% compared to the conventional passive-elastic prostheses evaluated (Flex-Foot Ceterusregand Freedom Innovations Sierra), even though the powered system is over twofold heavier than the conventional devices. These results highlight the clinical importance of prosthetic interventions that closely mimic the mass distribution, kinetics, and kinematics of the missing limb.

In this paper we describe the design and preliminary evaluation of an energetically-autonomous powered knee exoskeleton to facilitate running. The device consists of a knee brace in which a motorized mechanism actively places and removes a spring in parallel with the knee joint. This mechanism is controlled such that the spring is in parallel with the knee joint from approximately heel-strike to toe-off, and is removed from this state during the swing phase of running. In this way, the spring is intended to store energy at heel-strike which is then released when the heel leaves the ground, reducing the effort required by the quadriceps to exert this energy, thereby reducing the metabolic cost of running.

In the nearly six decades since researchers began to explore methods of creating them, exoskeletons have progressed from the stuff of science fiction to nearly commercialized products. While there are still many challenges associated with exoskeleton development that have yet to be perfected, the advances in the field have been enormous. In this paper, we review the history and discuss the state-of-the-art of lower limb exoskeletons and active orthoses. We provide a design overview of hardware, actuation, sensory, and control systems for most of the devices that have been described in the literature, and end with a discussion of the major advances that have been made and hurdles yet to be overcome.

Although below-knee prostheses have been commercially available for some time, today's devices are completely passive, and consequently, their mechanical properties remain fixed with walking speed and terrain. A lack of understanding of the ankle-foot biomechanics and the dynamic interaction between an amputee and a prosthesis is one of the main obstacles in the development of a biomimetic ankle-foot prosthesis. In this paper, we present a novel ankle-foot emulator system for the study of human walking biomechanics. The emulator system is comprised of a high performance, force-controllable, robotic ankle-foot worn by an amputee interfaced to a mobile computing unit secured around his waist. We show that the system is capable of mimicking normal ankle-foot walking behaviour. An initial pilot study supports the hypothesis that the emulator may provide a more natural gait than a conventional passive prosthesis

In this investigation we put forth a simple model to quantify the capacity of series elasticity to increase peak power output from an actuator. Using a linear bandwidth limited force source, we show how series spring stiffness and source stroke length effect power output to an inertial load. We show that an appropriate spring constant increases the peak power delivered to the inertial load over a limited stroke. The series elasticity changes the actuator operating point along its force-velocity curve and therefore effects the actuator work output over a fixed stroke length. For single shot motions, the peak power can increase by a factor of radic2 for appropriate series spring stiffness. We also present an example of how this work relates to human ankle function and it implies for the design of robotic or prosthetic ankles

Metabolic studies have shown that there is a metabolic cost associated with carrying load. Several leg exoskeletons have been developed by various groups in an attempt to augment the load carrying capability of the human. Previous research efforts have not fully exploited the passive dynamics of walking and have largely focused on fully actuated exoskeletons that are heavy with large energy requirements. In this paper, a lightweight, underactuated exoskeleton design is presented that runs in parallel to the human and supports the weight of a payload. Two exoskeleton architectures are pursued based on examining human walking data. A first architecture consists of springs at the hip, a variable impedance device at the knee, and springs at the ankle. A second architecture replaces the springs at the hip with a non-conservative actuator to examine the effect of adding power at desired instances throughout the gait cycle. Preliminary studies show that an efficient, underactuated leg exoskeleton can effectively transmit payload forces to the ground during the walking cycle

In this paper, we seek to understand how leg muscles and tendons work mechanically during walking in order to motivate the design of efficient robotic legs. We hypothesize that a robotic leg comprising only knee and ankle passive and quasi-passive elements, including springs, clutches and variable-damping components, can capture the dominant mechanical behavior of the human knee and ankle during level-ground walking at self-selected speeds. As a preliminary evaluation of this hypothesis, we put forth a simple leg model that captures the gross features of the human leg musculoskeletal architecture. We vary model parameters, or spring constants, damping levels and times when clutches are engaged, using an optimization scheme where errors between model joint behaviours and biological joint mechanics are minimized. For model evaluation, kinetic and kinematic gait data are employed from a single participant walking across a level-ground surface at a self-selected gait speed (1.3 m/sec). With only a single hip actuator, we find good agreement between model predictions and experimental gait data, suggesting that knee and ankle actuators are not necessary for level-ground robotic ambulation at self-selected gait speeds. This result is in support of the idea that muscles that span the human knee and ankle mainly operate eccentrically or isometrically, affording the relatively high metabolic walking economy of humans

Metabolic studies have shown that there is a metabolic cost associated with carrying load (T. M. Griffen, et al., 2003). In previous work, a lightweight, underactuated exoskeleton has been described that runs in parallel to the human and supports the weight of a payload (C. J. Walsh, et al., 2006). A state-machine control strategy is written based on joint angle and ground-exoskeleton force sensing to control the joint actuation at this exoskeleton hip and knee. The joint components of the exoskeleton in the sagittal plane consist of a force-controllable actuator at the hip, a variable-damper mechanism at the knee and a passive spring at the ankle. The control is motivated by examining human walking data. Positive, non-conservative power is added at the hip during the walking cycle to help propel the mass of the human and payload forward. At the knee, the damper mechanism is turned on at heel strike as the exoskeleton leg is loaded and turned off during terminal stance to allow knee flexion. The passive spring at the ankle engages in controlled dorsiflexion to store energy that is later released to assist in powered plantarflexion. Preliminary studies show that the state machines for the hip and knee work robustly and that the onset of walking can be detected in less than one gait cycle. Further, it is found that an efficient, underactuated leg exoskeleton can effectively transmit payload forces to the ground during the walking cycle

Advanced humanoid robots capable of operating in complex 3D environments likely utilize an online optimization strategy where joint accelerations are varied to achieve whole-body postural balance. To this end, we propose one such strategy that optimizes global body parameters such as spin angular momentum and body principal angles, or the angles between the inertia tensor principal axes and the lab frame axes. This optimization strategy is easily combined with other optimization objectives (e.g. maximal efficiency) subject to physical constraints such as requiring that the ZMP operates within the support base. To deal with Bellman's "curse of dimensionality" we suggest, in parallel, two computational simplifications that may make the optimization problem tractable and easily implemented on today's humanoid robots. Finally, we address the problem of support base planning during ground and aerial locomotory phases. We propose novel online strategies for robust coordination of interacting limbs compatible with the proposed optimization strategy.

Motivated by biomechanical studies on human walking, we present a control strategy for biologically realistic walking based on the principle of spin angular momentum regulation. Using a morphologically realistic human model and kinematic gait data, we compute the total spin angular momentum at a self-selected walking speed for one human test subject. We find that dimensionless spin angular momentum remains small (S/sub 1//(mass height velocity) < 0.02) throughout the gait cycle, and maximum whole body angular excursions within sagittal (<1/spl deg/), coronal (<0.2/spl deg/), and transverse (<2/spl deg/) planes are negligible. These data support the hypothesis that spin angular momentum in human walking is highly regulated by the central nervous system, and that there exists a nonlinear coupling between ground reaction force, F~, center of mass position, r~/sub CM/ , and center of pressure location, r~/sub CP/, or F~ = (FZ/sub ///Z/sub CM/)(r~/sub CM/ -r~/sub CP/). We employ this relationship to rapidly generate biologically realistic CP and CM reference trajectories. Using an open loop optimization strategy, we show that biologically realistic leg joint kinematics emerge through the minimization of spin angular momentum and the total sum of joint torque squared, suggesting that both angular momentum and energetic factors are important considerations for biomimetic controllers.

We present an algorithm that provides enhanced flexibility and robustness in the control of single-leg humanoid standing through the coordination of stance leg ankle torques and stabilizing movements of non-contact limbs. Current control approaches generally assume the presence of explicitly specified joint reference trajectories or desired virtual force calculations that ignore system dynamics. Here we describe a practical controller that 1) simplifies control of abstract variables such as the center of mass location using a two-stage model-based plant linearization; 2) determines motion of non-contact limbs useful for achieving control targets while satisfying dynamic balance constraints; and 3) provides robustness to modeling error using a sliding controller. The controller is tested with a morphologically realistic, 3-dimensional, 18 degree-of-freedom humanoid model serving as the plant. It is demonstrated that the controller can use less detailed control targets, and reject stronger disturbances, than previously implemented controllers that employ desired virtual forces and static body calculations.