Effect of Low-Pass Filtering on Passivity and Rendering Performance of Series Elastic Actuation.

We study the effect of low-pass filtering on the passivity and performance of series elastic actuation (SEA) under velocity-sourced impedance control (VSIC) while rendering virtual linear springs and the null impedance. We analytically derive the necessary and sufficient conditions for the passivity of SEA under VSIC with filters in the loop. We demonstrate that low-pass filtered velocity feedback of the inner motion controller amplifies the noise at the outer force loop, necessitating the force controller also be equipped with low-pass filtering. We derive passive physical equivalents of the closed-loop systems to provide intuitive explanations of the passivity bounds and to rigorously compare the performance of controllers with and without low-pass filtering. We show that, while low-pass filtering improves the rendering performance by decreasing the parasitic damping effects and allowing for higher motion controller gains, it also introduces more strict bounds on the range of passively renderable stiffness. We experimentally verify the passive stiffness rendering bounds and performance improvements for SEA under VSIC with filtered velocity feedback.

A Fundamental Limitation of Passive Spring Rendering With Series Elastic Actuation.

We establish a fundamental limitation of stiffness rendering with series elastic actuation by rigorously proving that no causal controller can passively render virtual stiffness levels that are higher than the stiffness of the physical series elastic element. To relax this bound, we propose the addition of a viscous damping term parallel to the elastic element to form series damped elastic actuation (SDEA). We show that there exist LTI controllers for SDEA that can relax the passivity bound on the virtual stiffness, and derive the necessary and sufficient conditions for the passive stiffness rendering with SDEA under such a controller. We experimentally verify the relaxed passive stiffness rendering bounds for SDEA, by studying the coupled stability of interactions with most destabilizing environments.

Preference-Based Human-in-the-Loop Optimization for Perceived Realism of Haptic Rendering.

The fidelity of haptic rendering is characterized by the perceived realism capturing the level of similarity to a corresponding tangible object. Perceived realism depends on the musculoskeletal, mental, and perceptual properties of the individuals that manipulate the system. Human-in-the-loop (HiL) studies provide a feasible means for the concurrent optimization of the performance of the overall haptic rendering process, as the physical limitations of the hardware, the factors affecting the fidelity of the rendering algorithm, and the limitations of human action and perception can all be considered simultaneously. In this study, we propose the use of preference-based HiL optimization techniques based on sample-efficient Bayesian optimization algorithms and qualitative pairwise comparisons to maximize the perceived realism of haptic rendering tasks. We present two HiL optimization studies that maximize the perceived realism of spring and friction rendering and validate our results by comparing the HiL-optimized rendering models with expert-tuned nominal models. We show that the system parameters can effectively be optimized within a reasonable amount of time using a preference-based HiL optimization approach. Furthermore, we demonstrate that the approach provides an efficient means of studying the effect of haptic rendering parameters on perceived realism by capturing the interactions among the parameters, even for relatively high dimensional parameter spaces.

Design, Implementation, and Evaluation of a Variable Stiffness Transradial Hand Prosthesis.

We present the design, implementation, and experimental evaluation of a low-cost, customizable, easy-to-use transradial hand prosthesis capable of adapting its compliance. Variable stiffness actuation (VSA) of the prosthesis is based on antagonistically arranged tendons coupled to nonlinear springs driven through a Bowden cable based power transmission. Bowden cable based antagonistic VSA can, not only regulate the stiffness and the position of the prosthetic hand but also enables a light-weight and low-cost design, by the opportunistic placement of motors, batteries, and controllers on any convenient location on the human body, while nonlinear springs are conveniently integrated inside the forearm. The transradial hand prosthesis also features tendon driven underactuated compliant fingers that allow natural adaption of the hand shape to wrap around a wide variety of object geometries, while the modulation of the stiffness of their drive tendons enables the prosthesis to perform various tasks with high dexterity. The compliant fingers of the prosthesis add inherent robustness and flexibility, even under impacts. The control of the variable stiffness transradial hand prosthesis is achieved by an sEMG based natural human-machine interface.

sEMG-Based Natural Control Interface for a Variable Stiffness Transradial Hand Prosthesis.

We propose, implement, and evaluate a natural human-machine control interface for a variable stiffness transradial hand prosthesis that achieves tele-impedance control through surface electromyography (sEMG) signals. This interface, together with variable stiffness actuation (VSA), enables an amputee to modulate the impedance of the prosthetic limb to properly match the requirements of a task while performing activities of daily living (ADL). Both the desired position and stiffness references are estimated through sEMG signals and used to control the VSA hand prosthesis. In particular, regulation of hand impedance is managed through the impedance measurements of the intact upper arm; this control takes place naturally and automatically as the amputee interacts with the environment, while the position of the hand prosthesis is regulated intentionally by the amputee through the estimated position of the shoulder. The proposed approach is advantageous since the impedance regulation takes place naturally without requiring amputees' attention and diminishing their functional capability. Consequently, the proposed interface is easy to use, does not require long training periods or interferes with the control of intact body segments. This control approach is evaluated through human subject experiments conducted over able volunteers where adequate estimation of references and independent control of position and stiffness are demonstrated.

Passivity of Series Elastic Actuation Under Model Reference Force Control During Null Impedance Rendering.

Series elastic actuation (SEA) is an interaction control paradigm that relies on a compliant force sensing element and utilizes the model of this compliant dynamics in closed-loop force control. We present sufficient conditions for passivity of SEA under model reference force control (MRFC) during null impedance rendering. We prove that overestimation of robot inertia and underestimation of the stiffness of the series elastic element can ensure coupled stability of interaction for SEA under MRFC during null impedance rendering, as long as a lower limit on damping compensation is not violated. We experimentally verify the passivity bounds and demonstrate the null impedance rendering performance of MRFC.

Physical Human-Robot Interaction Using HandsOn-SEA: An Educational Robotic Platform With Series Elastic Actuation.

For gaining proficiency in physical human-robot interactions, it is crucial for engineering students to be provided with the opportunity to gain hands-on experience with robotic devices that feature kinesthetic feedback. In this article, we propose HandsOn-SEA, a low-cost, single degree-of-freedom, force-controlled educational robot with series elastic actuation and introduce educational modules for the use of the device to allow students to experience the fundamental performance trade-offs inherent in robotic systems. The novelty of the proposed robot is due to the deliberate introduction of a compliant element between the actuator and the handle, whose deflections are measured to perform closed-loop force control. As an admittance-type robot, HandsOn-SEA relies on force feedback to achieve the desired level of safety and transparency and complements the existing impedance-type educational robots. We present the integration of HandsOn-SEA into the robotics curriculum, by providing guidelines for its use in a senior level robotics course, to help students experience the challenges involved in the synergistic design and control of robotic devices. We systematically evaluate the efficacy of the device in a robotics course delivered for five semesters and provide evidence that HandsOn-SEA is effective in instilling fundamental concepts and trade-offs in the design and control of robotic devices.

VnStylus: A Haptic Stylus With Variable Tip Compliance.

Variable stiffness tools have been shown to be advantageous for ensuring safety and improving stability, dynamic performance and energy efficiency of interaction tasks. In this article, we present the design, mathematical modeling, implementation, characterization and user evaluations of VnStylus, a stylus with hardware-based tip compliance modulation. The stiffness modulation of the stylus tip is achieved through transverse stiffness variations of axially loaded beams. This approach of mechanically-controlled stiffness variation is advantageous for a variable stiffness stylus, as it can be implemented using a fully compliant mechanism that alleviates the problem of friction forces dominating under miniaturization and allows for high fidelity stiffness display even for very low stiffness values. Thanks to its hardware-based impedance modulation, the device does not suffer from the bandwidth and the stable impedance rendering limitations of software-based impedance control strategies. Featuring a manual adjustment mechanism, the device does not necessitate actuators, sensor or electronics; hence, is lightweight, low cost, and robust. Experimental characterizations verify the large range of stiffness modulation that can be achieved and the accuracy of the equivalent stiffness model of the system. Human subject experiments provide evidence of the efficacy of the modulated stylus stiffness on human performance during several common interactions with styli.

Efficacy of Haptic Pedal Feel Compensation on Driving With Regenerative Braking.

In this article, we study the efficacy of haptic pedal feel compensation on driving safety and performance during regenerative braking. In particular, we evaluate the effectiveness of the preservation of the natural brake pedal feel under two-pedal cooperative braking and one-pedal driving scenarios, through human subject experiments in a simulated vehicle pursuit task. The experimental results indicate that pedal feel compensation can significantly decrease the hard braking instances, improving safety for both two-pedal cooperative braking and one-pedal driving conditions. Volunteers strongly prefer compensation, while they equally prefer and can effectively utilize two-pedal and one-pedal driving conditions. The beneficial effects of haptic pedal feel compensation on safety is evaluated to be larger for the two-pedal cooperative braking condition, as lack of compensation results in stiffening/softening pedal feel characteristics in this case.

Stable Physical Human-Robot Interaction Using Fractional Order Admittance Control.

In the near future, humans and robots are expected to perform collaborative tasks involving physical interaction in various environments, such as homes, hospitals, and factories. Robots are good at precision, strength, and repetition, while humans are better at cognitive tasks. The concept, known as physical human-robot interaction (pHRI), takes advantage of these abilities and is highly beneficial by bringing speed, flexibility, and ergonomics to the execution of complex tasks. Current research in pHRI focuses on designing controllers and developing new methods which offer a better tradeoff between robust stability and high interaction performance. In this paper, we propose a new controller, fractional order admittance controller, for pHRI systems. The stability and transparency analyses of the new control system are performed computationally with human-in-the-loop. Impedance matching is proposed to map fractional order control parameters to integer order ones, and then the stability robustness of the system is studied analytically. Furthermore, the interaction performance is investigated experimentally through two human subject studies involving continuous contact with linear and nonlinear viscoelastic environments. The results indicate that the fractional order admittance controller can be made more robust and transparent than the integer order admittance controller and the use of fractional order term can reduce the human effort during tasks involving contact interactions with environment.

Electroencephalographic identifiers of motor adaptation learning.

OBJECTIVE: Recent brain-computer interface (BCI) assisted stroke rehabilitation protocols tend to focus on sensorimotor activity of the brain. Relying on evidence claiming that a variety of brain rhythms beyond sensorimotor areas are related to the extent of motor deficits, we propose to identify neural correlates of motor learning beyond sensorimotor areas spatially and spectrally for further use in novel BCI-assisted neurorehabilitation settings. APPROACH: Electroencephalographic (EEG) data were recorded from healthy subjects participating in a physical force-field adaptation task involving reaching movements through a robotic handle. EEG activity recorded during rest prior to the experiment and during pre-trial movement preparation was used as features to predict motor adaptation learning performance across subjects. MAIN RESULTS: Subjects learned to perform straight movements under the force-field at different adaptation rates. Both resting-state and pre-trial EEG features were predictive of individual adaptation rates with relevance of a broad network of beta activity. Beyond sensorimotor regions, a parieto-occipital cortical component observed across subjects was involved strongly in predictions and a fronto-parietal cortical component showed significant decrease in pre-trial beta-powers for users with higher adaptation rates and increase in pre-trial beta-powers for users with lower adaptation rates. SIGNIFICANCE: Including sensorimotor areas, a large-scale network of beta activity is presented as predictive of motor learning. Strength of resting-state parieto-occipital beta activity or pre-trial fronto-parietal beta activity can be considered in BCI-assisted stroke rehabilitation protocols with neurofeedback training or volitional control of neural activity for brain-robot interfaces to induce plasticity.

Rehabilitation robotics ontology on the cloud.

We introduce the first formal rehabilitation robotics ontology, called RehabRobo-Onto, to represent information about rehabilitation robots and their properties; and a software system RehabRobo-Query to facilitate access to this ontology. RehabRobo-Query is made available on the cloud, utilizing Amazon Web services, so that 1) rehabilitation robot designers around the world can add/modify information about their robots in RehabRobo-Onto, and 2) rehabilitation robot designers and physical medicine experts around the world can access the knowledge in RehabRobo-Onto by means of questions about robots, in natural language, with the guide of the intelligent userinterface of RehabRobo-Query. The ontology system consisting of RehabRobo-Onto and RehabRobo-Query is of great value to robot designers as well as physical therapists and medical doctors. On the one hand, robot designers can access various properties of the existing robots and to the related publications to further improve the state-of-the-art. On the other hand, physical therapists and medical doctors can utilize the ontology to compare rehabilitation robots and to identify the ones that serve best to cover their needs, or to evaluate the effects of various devices for targeted joint exercises on patients with specific disorders.

Brain Computer Interface based robotic rehabilitation with online modification of task speed.

We present a systematic approach that enables online modification/adaptation of robot assisted rehabilitation exercises by continuously monitoring intention levels of patients utilizing an electroencephalogram (EEG) based Brain-Computer Interface (BCI). In particular, we use Linear Discriminant Analysis (LDA) to classify event-related synchronization (ERS) and desynchronization (ERD) patterns associated with motor imagery; however, instead of providing a binary classification output, we utilize posterior probabilities extracted from LDA classifier as the continuous-valued outputs to control a rehabilitation robot. Passive velocity field control (PVFC) is used as the underlying robot controller to map instantaneous levels of motor imagery during the movement to the speed of contour following tasks. In other words, PVFC changes the speed of contour following tasks with respect to intention levels of motor imagery. PVFC also allows decoupling of the task and the speed of the task from each other, and ensures coupled stability of the overall robot patient system. The proposed framework is implemented on AssistOn-Mobile--a series elastic actuator based on a holonomic mobile platform, and feasibility studies with healthy volunteers have been conducted test effectiveness of the proposed approach. Giving patients online control over the speed of the task, the proposed approach ensures active involvement of patients throughout exercise routines and has the potential to increase the efficacy of robot assisted therapies.

Passive velocity field control of a forearm-wrist rehabilitation robot.

This paper presents design, implementation and control of a 3RPS-R exoskeleton, specifically built to impose targeted therapeutic exercises to forearm and wrist. Design of the exoskeleton features enhanced ergonomy, enlarged workspace and optimized device performance when compared to previous versions of the device. Passive velocity field control (PVFC) is implemented at the task space of the manipulator to provide assistance to the patients, such that the exoskeleton follows a desired velocity field asymptotically while maintaining passivity with respect to external applied torque inputs. PVFC is augmented with virtual tunnels and resulting control architecture is integrated into a virtual flight simulator with force-feedback. Experimental results are presented indicating the applicability and effectiveness of using PVFC on 3RPS-R exoskeleton to deliver therapeutic movement exercises.