Soft robots actuated by pressurization and inflation of a pneumatic network (a "pneunet") of small channels in elastomeric materials are appealing for their ability to produce sophisticated motions with simple controls. Although current designs of pneu-nets achieve motion with large amplitudes, they do so relatively slowly (that is, over seconds). This paper describes a new design for pneu-nets that reduces the amount of gas that must be transported for inflation of the pneu-net, and thus increases its speed of actuation. A simple actuator can bend from a linear shape to a quasi-circular shape in 50 milliseconds when pressurized at ΔP = 345 kPa. At high rates of pressurization and inflation, the path along which the actuator bends depends on this rate. When inflated fully, the channels and chambers of this new pneu-net design experience only one-tenth the change in volume of that required for a motion of equal amplitude using the previous design. This small change in volume requires comparably low levels of strain in the material at maximum amplitudes of actuation, and commensurately low rates of fatigue and failure. This actuator can operate over a million cycles without significant degradation of performance. This design for soft robotic actuators combines high rates of actuation with high reliability of the actuator, and opens new areas of application for them.

This paper presents a portable, assistive, soft robotic glove designed to augment hand rehabilitation for individuals with functional grasp pathologies. The robotic glove utilizes soft actuators consisting of molded elastomeric chambers with fiber reinforcements that induce specific bending, twisting and extending trajectories under fluid pressurization. These soft actuators were mechanically programmed to match and support the range of motion of individual fingers. They demonstrated the ability to generate significant force when pressurized and exhibited low impedance when un-actuated. To operate the soft robotic glove, a control hardware system was designed and included fluidic pressure sensors in line with the hydraulic actuators and a closed-loop controller to regulate the pressure. Demonstrations with the complete system were performed to evaluate the ability of the soft robotic glove to carry out gross and precise functional grasping. Compared to existing devices, the soft robotic glove has the potential to increase user freedom and independence through its portable waist belt pack and open palm design.

Soft fluidic actuators consisting of elastomeric matrices with embedded flexible materials are of particular interest to the robotics community because they are affordable and can be easily customized to a given application. However, the significant potential of such actuators is currently limited as their design has typically been based on intuition. In this paper, the principle of operation of these actuators is comprehensively analyzed and described through experimentally validated quasi-static analytical and finite-element method models for bending in free space and force generation when in contact with an object. This study provides a set of systematic design rules to help the robotics community create soft actuators by understanding how these vary their outputs as a function of input pressure for a number of geometrical parameters. Additionally, the proposed analytical model is implemented in a controller demonstrating its ability to convert pressure information to bending angle in real time. Such an understanding of soft multimaterial actuators will allow future design concepts to be rapidly iterated and their performance predicted, thus enabling new and innovative applications that produce more complex motions to be explored. , where he specializes in soft robotic systems that find application in wearables, medical, and rehabilitation areas.Zheng Wang (M'10) received the B.Sc. degree (with merit) from Tsinghua University, Beijing, China; the M.Sc. degree (with distinction) from Imperial College London, London, U.K.; and the Ph.D. degree (with merit) from . His research interest include haptics human-robot interaction, teleoperation, cable-driven mechanisms, and soft robotics.Johannes T. B. Overvelde received the B.Sc. and M.Sc. degrees (both with distinction) in mechanical engineering from Delft University of Technology, Delft, The Netherlands, in 2012. He is currently working toward the Ph.D. degree in applied mathematics with Katiabridge. He is the Founder of the Harvard Biodesign Laboratory, which brings together researchers from the engineering, industrial design, apparel, clinical, and business communities to develop new technologies and translate them to industrial partners. His research focuses on new approaches to the design, manufacture, and control of soft wearable robotic devices for augmenting and restoring human performance, and evaluating them through biomechanical and physiological studies.

Stroke-induced hemiparetic gait is characteristically slow and metabolically expensive. Passive assistive devices such as ankle-foot orthoses are often prescribed to increase function and independence after stroke; however, walking remains highly impaired despite-and perhaps because of-their use. We sought to determine whether a soft wearable robot (exosuit) designed to supplement the paretic limb's residual ability to generate both forward propulsion and ground clearance could facilitate more normal walking after stroke. Exosuits transmit mechanical power generated by actuators to a wearer through the interaction of garment-like, functional textile anchors and cable-based transmissions. We evaluated the immediate effects of an exosuit actively assisting the paretic limb of individuals in the chronic phase of stroke recovery during treadmill and overground walking. Using controlled, treadmill-based biomechanical investigation, we demonstrate that exosuits can function in synchrony with a wearer's paretic limb to facilitate an immediate 5.33 ± 0.91°increase in the paretic ankle's swing phase dorsiflexion and 11 ± 3% increase in the paretic limb's generation of forward propulsion (P < 0.05). These improvements in paretic limb function contributed to a 20 ± 4% reduction in forward propulsion interlimb asymmetry and a 10 ± 3% reduction in the energy cost of walking, which is equivalent to a 32 ± 9% reduction in the metabolic burden associated with poststroke walking. Relatively low assistance (~12% of biological torques) delivered with a lightweight and nonrestrictive exosuit was sufficient to facilitate more normal walking in ambulatory individuals after stroke. Future work will focus on understanding how exosuit-induced improvements in walking performance may be leveraged to improve mobility after stroke.

Wearable robotic devices have been shown to substantially reduce the energy expenditure of human walking. However, response variance between participants for fixed control strategies can be high, leading to the hypothesis that individualized controllers could further improve walking economy. Recent studies on human-in-the-loop (HIL) control optimization have elucidated several practical challenges, such as long experimental protocols and low signal-to-noise ratios. Here, we used Bayesian optimization-an algorithm well suited to optimizing noisy performance signals with very limited data-to identify the peak and offset timing of hip extension assistance that minimizes the energy expenditure of walking with a textile-based wearable device. Optimal peak and offset timing were found over an average of 21.4 ± 1.0 min and reduced metabolic cost by 17.4 ± 3.2% compared with walking without the device (mean ± SEM), which represents an improvement of more than 60% on metabolic reduction compared with state-of-the-art devices that only assist hip extension. In addition, our results provide evidence for participant-specific metabolic distributions with respect to peak and offset timing and metabolic landscapes, lending support to the hypothesis that individualized control strategies can offer substantial benefits over fixed control strategies. These results also suggest that this method could have practical impact on improving the performance of wearable robotic devices.