High-performance actuators are crucial to enable mechanical versatility of wearable robots, which are required to be lightweight, highly backdrivable, and with high bandwidth. State-of-the-art actuators, e.g., series elastic actuators (SEAs), have to compromise bandwidth to improve compliance (i.e., backdrivability). We describe the design and human-robot interaction modeling of a portable hip exoskeleton based on our custom quasi-direct drive (QDD) actuation (i.e., a high torque density motor with low ratio gear). We also present a model-based performance benchmark comparison of representative actuators in terms of torque capability, control bandwidth, backdrivability, and force tracking accuracy. This paper aims to corroborate the underlying philosophy of “design for control“, namely meticulous robot design can simplify control algorithms while ensuring high performance. Following this idea, we create a lightweight bilateral hip exoskeleton to reduce joint loadings during normal activities, including walking and squatting. Experiments indicate that the exoskeleton is able to produce high nominal torque (17.5 Nm), high backdrivability (0.4 Nm backdrive torque), high bandwidth (62.4 Hz), and high control accuracy (1.09 Nm root mean square tracking error, 5.4% of the desired peak torque). Its controller is versatile to assist walking at different speeds and squatting. This work demonstrates performance improvement compared with state-of-the-art exoskeletons.
Spine-Inspired Continuum Soft Exoskeleton for Stoop Lifting Assistance
Back injuries are the most prevalent work-related musculoskeletal disorders and represent a major cause of disability and socio-economic problems. Although innovations in wearable robots aim to alleviate this hazard, the majority of existing exoskeletons are obtrusive because the rigid linkage design limits natural movement, thus causing ergonomic risk. Moreover, these existing systems are typically only suitable for one type of movement assistance, not ubiquitous for a wide variety of activities. To fill in this gap, this paper presents a new wearable robot design approach continuum soft exoskeleton. This wearable robot is unobtrusive and assists both squat and stoops while not impeding walking motion. To tackle the challenge of the unique anatomy of spine, our robot is conformal to human anatomy and it can reduce multiple types of forces along the human spine such as the spinae muscle force, shear, and compression force of the lumbar vertebrae. We derived kinematics and kinetics models of this mechanism and established an analytical biomechanics model of human-robot interaction. Quantitative analysis of disc compression force, disc shear force and muscle force was performed in simulation. We further developed a virtual impedance control strategy to deliver force control and compensate hysteresis of Bowden cable transmission. The more »
- Award ID(s):
- 1830613
- Publication Date:
- NSF-PAR ID:
- 10112268
- Journal Name:
- IEEE Robotics and Automation Letters
- Page Range or eLocation-ID:
- 1 to 1
- ISSN:
- 2377-3774
- Sponsoring Org:
- National Science Foundation
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Passive trunk exoskeletons support the human body with mechanical elements like springs and trunk compression, allowing them to guide motion and relieve the load on the spine. However, to provide appropriate support, elements of the exoskeleton (e.g., degree of compression) should be intelligently adapted to the current task. As it is not currently clear how adjusting different exoskeleton elements affects the wearer, this study preliminarily examines the effects of simultaneously adjusting both exoskeletal spinal column stiffness and trunk compression in a passive trunk exoskeleton. Six participants performed four dynamic tasks (walking, sit-to-stand, lifting a 20-lb box, lifting a 40-lb box) and experienced unexpected perturbations both without the exoskeleton and in six exoskeleton configurations corresponding to two compression levels and three stiffness levels. While results are preliminary due to the small sample size and relatively small increases in stiffness, they indicate that both compression and stiffness may affect kinematics and electromyography, that the effects may differ between activities, and that there may be interaction effects between stiffness and compression. As the next step, we will conduct a larger study with the same protocol more participants and larger stiffness increases to systematically evaluate the effects of different exoskeleton characteristics on the wearer.Clinicalmore »
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While tremendous advances in visual and auditory realism have been made for virtual and augmented reality (VR/AR), introducing a plausible sense of physicality into the virtual world remains challenging. Closing the gap between real-world physicality and immersive virtual experience requires a closed interaction loop: applying user-exerted physical forces to the virtual environment and generating haptic sensations back to the users. However, existing VR/AR solutions either completely ignore the force inputs from the users or rely on obtrusive sensing devices that compromise user experience. By identifying users' muscle activation patterns while engaging in VR/AR, we design a learning-based neural interface for natural and intuitive force inputs. Specifically, we show that lightweight electromyography sensors, resting non-invasively on users' forearm skin, inform and establish a robust understanding of their complex hand activities. Fuelled by a neural-network-based model, our interface can decode finger-wise forces in real-time with 3.3% mean error, and generalize to new users with little calibration. Through an interactive psychophysical study, we show that human perception of virtual objects' physical properties, such as stiffness, can be significantly enhanced by our interface. We further demonstrate that our interface enables ubiquitous control via finger tapping. Ultimately, we envision our findings to push forward researchmore »
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Measurement of interaction forces distributed across the attachment interface in wearable devices is critical for understanding ergonomic physical human–robot interaction (pHRI). The main challenges in sensorization of pHRI interfaces are (i) capturing the fine nature of force transmission from compliant human tissue onto rigid surfaces in the wearable device and (ii) utilizing a low-cost and easily implementable design that can be adapted for a variety of human interfaces. This paper addresses both challenges and presents a modular sensing panel that uses force-sensing resistors (FSRs) combined with robust electrical and mechanical integration principles that result in a reliable solution for distributed load measurement. The design is demonstrated through an upper-arm cuff, which uses 24 sensing panels, in conjunction with the Harmony exoskeleton. Validation of the design with controlled loading of the sensorized cuff proves the viability of FSRs in an interface sensing solution. Preliminary experiments with a human subject highlight the value of distributed interface force measurement in recognizing the factors that influence ergonomic pHRI and elucidating their effects. The modular design and low cost of the sensing panel lend themselves to extension of this approach for studying ergonomics in a variety of wearable applications with the goal of achieving safe,more »
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Accepted Manuscript1.0
- Publisher's Version of Record
- https://doi.org/10.1109/LRA.2019.2935351
