AdjuSST: An Adjustable Surface Stiffness Treadmill

Humans have the remarkable ability to manage foot-ground interaction seamlessly across terrain changes despite the high dynamic complexity of the task. Understanding how adaptation in the neuromotor system enables this level of robustness in the face of changing interaction dynamics is critical for developing more effective gait retraining interventions. We developed an adjustable surface stiffness treadmill (AdjuSST) to trigger these adaptation mechanisms and enable studies to better understand human adaptation to changing foot-ground dynamics. The AdjuSST system makes use of fundamental beam-bending principles; it controls surface stiffness by controlling the effective length of a cantilever beam. The beam acts as a spring suspension for the transverse endpoint load applied through the treadmill. The system is capable of enforcing a stiffness range of 15-300kN/m within 340 ms, deflecting linearly downwards up to 10 cm, and comfortably accommodating two full steps of travel along the belt. AdjuSST offers significant enhancements in effective walking surface length compared to similar systems, while also maintaining a useful stiffness range and responsive spring suspension. These improvements enhance our ability to study locomotor control and adaptation to changes in surface stiffness, as well as provide new avenues for gait rehabilitation.

Design and Backdrivability Modeling of a Portable High Torque Robotic Knee Prosthesis With Intrinsic Compliance For Agile Activities

High-performance prostheses are crucial to enable versatile activities like walking, squatting, and running for lower extremity amputees. State-of-the-art prostheses are either not powerful enough to support demanding activities or have low compliance (low backdrivability) due to the use of high speed ratio transmission. Besides speed ratio, gearbox design is also crucial to the compliance of wearable robots, but its role is typically ignored in the design process. This paper proposed an analytical backdrive torque model that accurately estimate the backdrive torque from both motor and transmission to inform the robot design. Following this model, this paper also proposed methods for gear transmission design to improve compliance by reducing inertia of the knee prosthesis. We developed a knee prosthesis using a high torque actuator (built-in 9:1 planetary gear) with a customized 4:1 low-inertia planetary gearbox. Benchtop experiments show the backdrive torque model is accurate and proposed prosthesis can produce 200 Nm high peak torque (shield temperature <60°C), high compliance (2.6 Nm backdrive torque), and high control accuracy (2.7/8.1/1.7 Nm RMS tracking errors for 1.25 m/s walking, 2 m/s running, and 0.25 Hz squatting, that are 5.4%/4.1%/1.4% of desired peak torques). Three able-bodied subject experiments showed our prosthesis could support agile and high-demanding activities.

Theory of Fast Walking With Human-Driven Load-Carrying Robot Exoskeletons

Reaching and maintaining high walking speeds is challenging for a human when carrying extra weight, such as walking with a heavy backpack. Robotic limbs can support a heavy backpack when standing still, but accelerating a backpack within a couple of steps to race-walking speeds requires limb force and energy beyond natural human ability. Here, we conceive a human-driven robot exoskeleton that could accelerate a heavy backpack faster and maintain top speeds higher than what the human alone can when not carrying a backpack. The key components of the exoskeleton are the mechanically adaptive but energetically passive spring limbs. We show that by optimally adapting the stiffness of the limbs, the robot can achieve near-horizontal center of mass motion to emulate the load-bearing mechanics of the bicycle. We find that such an exoskeleton could enable the human to accelerate one extra body weight up to top race-walking speeds in ten steps. Our finding predicts that human-driven mechanically adaptive robot exoskeletons could extend human weight-bearing and fast-walking ability without using external energy.

An Innovative Spiral Pulley that Optimizes Cable Tension Variation for Superior Balancing Performance

In modern manufacturing, the long-term handling of heavy objects is a main factor leading to muscle pain in the waist and lower back. Robots play an important role in reducing the burden on workers by compensating for the gravitational force. Energy-conserving passive mechanisms are commonly used in assistive robots because of their reliability and durability. One such mechanism is a spiral pulley and spring couple, which is a compact and reliable solution to provide a constant assistive force. A spiral pulley has a predesigned changing radius to balance the increasing restoring force of the spring as it extends. This allows the mechanism to exert a constant torque within the designed range. A crucial aspect of such a mechanism is the calculation of the shape of the spiral pulley. Accurate calculations enable the mechanism to provide a more optimal balancing ability. In this study, an innovative spiral pulley was designed by considering the cable tension variation along the cable attached to the pulley. The balancing performance of the proposed pulley was evaluated based on its accuracy in providing a balanced torque and an effective range. A comparative experiment using a conventional spiral pulley confirmed the effectiveness of the proposed pulley.

Modeling and Stiffness-based Continuous Torque Control of Lightweight Quasi-Direct-Drive Knee Exoskeletons for Versatile Walking Assistance

State-of-the-art exoskeletons are typically limited by low control bandwidth and small range stiffness of actuators which are based on high gear ratios and elastic components (e.g., series elastic actuators). Furthermore, most exoskeletons are based on discrete gait phase detection and/or discrete stiffness control resulting in discontinuous torque profiles. To fill these two gaps, we developed a portable lightweight knee exoskeleton using quasi-direct drive (QDD) actuation that provides 14 Nm torque (36.8% biological joint moment for overground walking). This paper presents 1) stiffness modeling of torque-controlled QDD exoskeletons and 2) stiffness-based continuous torque controller that estimates knee joint moment in real-time. Experimental tests found the exoskeleton had high bandwidth of stiffness control (16 Hz under 100 Nm/rad) and high torque tracking accuracy with 0.34 Nm Root Mean Square (RMS) error (6.22%) across 0-350 Nm/rad large range stiffness. The continuous controller was able to estimate knee moments accurately and smoothly for three walking speeds and their transitions. Experimental results with 8 able-bodied subjects demonstrated that our exoskeleton was able to reduce the muscle activities of all 8 measured knee and ankle muscles by 8.60%-15.22% relative to unpowered condition, and two knee flexors and one ankle plantar flexor by 1.92%-10.24% relative to baseline (no exoskeleton) condition.

Bioinspired Legged Robot Design via Blended Physical and Virtual Impedance Control

In order to approach the performance of biological locomotion in legged robots, better integration between body design and control is required. In that respect, understanding the mechanics and control of human locomotion will help us build legged robots with comparable efficient performance. From another perspective, developing bioinspired robots can also improve our understanding of human locomotion. In this work, we create a bioinspired robot with a blended physical and virtual impedance control to configure the robot’s mechatronic setup. We consider human neural control and musculoskeletal system a blueprint for a hopping robot. The hybrid electric-pneumatic actuator (EPA) presents an artificial copy of this biological system to implement the blended control. By defining efficacy as a metric that encompasses both performance and efficiency, we demonstrate that incorporating a simple force-based control besides constant pressure pneumatic artificial muscles (PAM) alone can increase the efficiency up to 21% in simulations and 7% in experiments with the 2-segmented EPA-hopper robot. Also, we show that with proper adjustment of the force-based controller and the PAMs, efficacy can be further increased to 41%. Finally, experimental results with the 3-segmented EPA-hopper robot and comparisons with human hopping confirm the extendability of the proposed methods to more complex robots.

Augmented Humanity: A Systematic Mapping Review

Augmented humanity (AH) is a term that has been mentioned in several research papers. However, these papers differ in their definitions of AH. The number of publications dealing with the topic of AH is represented by a growing number of publications that increase over time, being high impact factor scientific contributions. However, this terminology is used without being formally defined. The aim of this paper is to carry out a systematic mapping review of the different existing definitions of AH and its possible application areas. Publications from 2009 to 2020 were searched in Scopus, IEEE and ACM databases, using search terms "augmented human", "human augmentation" and "human 2.0". Of the 16,914 initially obtained publications, a final number of 133 was finally selected. The mapping results show a growing focus on works based on AH, with computer vision being the index term with the highest number of published articles. Other index terms are wearable computing, augmented reality, human-robot interaction, smart devices and mixed reality. In the different domains where AH is present, there are works in computer science, engineering, robotics, automation and control systems and telecommunications. This review demonstrates that it is necessary to formalize the definition of AH and also the areas of work with greater openness to the use of such concept. This is why the following definition is proposed: "Augmented humanity is a human-computer integration technology that proposes to improve capacity and productivity by changing or increasing the normal ranges of human function through the restoration or extension of human physical, intellectual and social capabilities".

Applying Hip Stiffness With an Exoskeleton to Compensate Gait Kinematics

Neurological disorders and aging induce impaired gait kinematics. Despite recent advances, effective methods using lower-limb exoskeleton robots to restore gait kinematics are as yet limited. In this study, applying virtual stiffness using a hip exoskeleton was investigated as a possible method to guide users to change their gait kinematics. With a view to applications in locomotor rehabilitation, either to provide assistance or promote recovery, this study assessed whether imposed stiffness induced changes in the gait pattern during walking; and whether any changes persisted upon removal of the intervention, which would indicate changes in central neuro-motor control. Both positive and negative stiffness induced immediate and persistent changes of gait kinematics. However, the results showed little behavioral evidence of persistent changes in neuro-motor control, not even short-lived aftereffects. In addition, stride duration was little affected, suggesting that at least two dissociable layers exist in the neuro-motor control of human walking. The lack of neuro-motor adaptation suggests that, within broad limits, the central nervous system is surprisingly indifferent to the details of lower limb kinematics. The lack of neuro-motor adaptation also suggests that alternative methods may be required to implement a therapeutic technology to promote recovery. However, the immediate, significant, and reproducible changes in kinematics suggest that applying hip stiffness with an exoskeleton may be an effective assistive technology for compensation.

Fuzzy torque trajectory control of a rotary series elastic actuator with nonlinear friction compensation

For humanoid/memetic robots, modeling and accurate torque trajectory control of a rotary series elastic actuator (RSEA) is of great importance. In this study, the fuzzy logic torque controller with nonlinear friction compensation (NLFC) is used to improve the deteriorating trajectory tracking performance caused by these nonlinear elements in RSEA systems. In order to demonstrate the power efficiency and performance of the proposed control system, several experiments have been performed on the experimental setup, including a torque motor with worm gear and torsional flat-double spiral spring (TFDSS). The proposed novel RSEA is designed and tested using different controllers, including PID feedforward controller (PID-FFC), fuzzy logic feedforward controller (FL-FFC), and fuzzy torque controller with friction compensation (FTC-FC). A comparative study among controllers is conducted to show the robustness of FTC-FC against a step and ramp-type disturbances. The simulation and experimental results here strongly confirm that the proposed control method produces better control performance.

A biarticular passive exosuit to support balance control can reduce metabolic cost of walking

Nowadays, the focus on the development of assistive devices just for people with mobility disorders has shifted towards enhancing physical abilities of able-bodied humans. As a result, the interest in the design of cheap and soft wearable exoskeletons (called exosuits) is distinctly growing. In this paper, a passive lower limb exosuit with two biarticular variable stiffness elements is introduced. These elements are in parallel to the hamstring muscles of the leg and controlled based on a new version of the FMCH (force modulated compliant hip) control framework in which the force feedback is replaced by the length feedback (called LMCH). The main insight to employ leg length feedback is to develop a passive exosuit. Fortunately, similar to FMCH, the LMCH method also predicts human-like balance control behaviours, such as the VPP (virtual pivot point) phenomenon, observed in human walking. Our simulation results, using a neuromuscular model of human walking, demonstrate that this method could reduce the metabolic cost of human walking by 10%. Furthermore, to validate the design and simulation results, a preliminary version of this exosuit comprised of springs with constant stiffness was built. An experiment with eight healthy subjects was performed. We made a comparison between the walking experiments while the exosuit is worn but the springs were slack and those when the appropriate springs were contributing. It shows that passive biarticular elasticity can result in a metabolic reduction of 14.7 [Formula: see text] 4.27%. More importantly, compared to unassisted walking (when exosuit is not worn), such a passive device can reduce walking metabolic cost by 4.68 [Formula: see text] 4.24%.

How to run 50% faster without external energy

Technological innovations may enable next-generation running shoes to provide unprecedented mobility. But how could a running shoe increase the speed of motion without providing external energy? We found that the top speed of running may be increased more than 50% using a catapult-like exoskeleton device, which does not provide external energy. Our finding uncovers the hidden potential of human performance augmentation via unpowered robotic exoskeletons. Our result may lead to a new-generation of augmentation devices developed for sports, rescue operations, and law enforcement, where humans could benefit from increased speed of motion.

The exoskeleton expansion: improving walking and running economy

Since the early 2000s, researchers have been trying to develop lower-limb exoskeletons that augment human mobility by reducing the metabolic cost of walking and running versus without a device. In 2013, researchers finally broke this 'metabolic cost barrier'. We analyzed the literature through December 2019, and identified 23 studies that demonstrate exoskeleton designs that improved human walking and running economy beyond capable without a device. Here, we reviewed these studies and highlighted key innovations and techniques that enabled these devices to surpass the metabolic cost barrier and steadily improve user walking and running economy from 2013 to nearly 2020. These studies include, physiologically-informed targeting of lower-limb joints; use of off-board actuators to rapidly prototype exoskeleton controllers; mechatronic designs of both active and passive systems; and a renewed focus on human-exoskeleton interface design. Lastly, we highlight emerging trends that we anticipate will further augment wearable-device performance and pose the next grand challenges facing exoskeleton technology for augmenting human mobility.