Leveraging Disturbance Observer Based Torque Control for Improved Impedance Rendering with Series Elastic Actuators

The fidelity with which series elastic actuators (SEAs) render desired impedances is important. Numerous approaches to SEA impedance control have been developed under the premise that high-precision actuator torque control is a prerequisite. Indeed, the design of an inner torque compensator has a significant impact on actuator impedance rendering. The disturbance observer (DOB) based torque control implemented in NASA's Valkyrie robot is considered here and a mathematical model of this torque control, cascaded with an outer impedance compensator, is constructed. While previous work has examined the impact a disturbance observer has on torque control performance, little has been done regarding DOBs and impedance rendering accuracy. Both simulation and a series of experiments are used to demonstrate the significant improvements possible in an SEA's ability to render desired dynamic behaviors when utilizing a DOB. Actuator transparency at low impedances is improved, closed loop hysteresis is reduced, and the actuator's dynamic response to both commands and interaction torques more faithfully matches that of the desired model. All of this is achieved by leveraging DOB based control rather than increasing compensator gains, thus making improved SEA impedance control easier to achieve in practice

W-FYD: a Wearable Fabric-based Display for Haptic Multi-Cue Delivery and Tactile Augmented Reality

Despite the importance of softness, there is no evidence of wearable haptic systems able to deliver controllable softness cues. Here, we present the Wearable Fabric Yielding Display (W-FYD), a fabric-based display for multi-cue delivery that can be worn on user's finger and enables, for the first time, both active and passive softness exploration. It can also induce a sliding effect under the finger-pad. A given stiffness profile can be obtained by modulating the stretching state of the fabric through two motors. Furthermore, a lifting mechanism allows to put the fabric in contact with the user's finger-pad, to enable passive softness rendering. In this paper, we describe the architecture of W-FYD, and a thorough characterization of its stiffness workspace, frequency response and softness rendering capabilities. We also computed device Just Noticeable Difference in both active and passive exploratory conditions, for linear and non-linear stiffness rendering as well as for sliding direction perception. The effect of device weight was also considered. Furthermore, performance of participants and their subjective quantitative evaluation in detecting sliding direction and softness discrimination tasks are reported. Finally, applications of W-FYD in tactile augmented reality for open palpation are discussed, opening interesting perspectives in many fields of human-machine interaction

Advancing proxy-based haptic feedback in virtual reality

This thesis advances haptic feedback for Virtual Reality (VR). Our work is guided by Sutherland's 1965 vision of the ultimate display, which calls for VR systems to control the existence of matter. To push towards this vision, we build upon proxy-based haptic feedback, a technique characterized by the use of passive tangible props. The goal of this thesis is to tackle the central drawback of this approach, namely, its inflexibility, which yet hinders it to fulfill the vision of the ultimate display. Guided by four research questions, we first showcase the applicability of proxy-based VR haptics by employing the technique for data exploration. We then extend the VR system's control over users' haptic impressions in three steps. First, we contribute the class of Dynamic Passive Haptic Feedback (DPHF) alongside two novel concepts for conveying kinesthetic properties, like virtual weight and shape, through weight-shifting and drag-changing proxies. Conceptually orthogonal to this, we study how visual-haptic illusions can be leveraged to unnoticeably redirect the user's hand when reaching towards props. Here, we contribute a novel perception-inspired algorithm for Body Warping-based Hand Redirection (HR), an open-source framework for HR, and psychophysical insights. The thesis concludes by proving that the combination of DPHF and HR can outperform the individual techniques in terms of the achievable flexibility of the proxy-based haptic feedback.Diese Arbeit widmet sich haptischem Feedback für Virtual Reality (VR) und ist inspiriert von Sutherlands Vision des ultimativen Displays, welche VR-Systemen die Fähigkeit zuschreibt, Materie kontrollieren zu können. Um dieser Vision näher zu kommen, baut die Arbeit auf dem Konzept proxy-basierter Haptik auf, bei der haptische Eindrücke durch anfassbare Requisiten vermittelt werden. Ziel ist es, diesem Ansatz die für die Realisierung eines ultimativen Displays nötige Flexibilität zu verleihen. Dazu bearbeiten wir vier Forschungsfragen und zeigen zunächst die Anwendbarkeit proxy-basierter Haptik durch den Einsatz der Technik zur Datenexploration. Anschließend untersuchen wir in drei Schritten, wie VR-Systeme mehr Kontrolle über haptische Eindrücke von Nutzern erhalten können. Hierzu stellen wir Dynamic Passive Haptic Feedback (DPHF) vor, sowie zwei Verfahren, die kinästhetische Eindrücke wie virtuelles Gewicht und Form durch Gewichtsverlagerung und Veränderung des Luftwiderstandes von Requisiten vermitteln. Zusätzlich untersuchen wir, wie visuell-haptische Illusionen die Hand des Nutzers beim Greifen nach Requisiten unbemerkt umlenken können. Dabei stellen wir einen neuen Algorithmus zur Body Warping-based Hand Redirection (HR), ein Open-Source-Framework, sowie psychophysische Erkenntnisse vor. Abschließend zeigen wir, dass die Kombination von DPHF und HR proxy-basierte Haptik noch flexibler machen kann, als es die einzelnen Techniken alleine können

Hap-Pro: a wearable haptic device for proprioceptive feedback

Objective: Myolectric hand prostheses have reached a considerable technological level and gained an increasing attention in assistive robotics. However, their abandonment rate remains high, with unintuitive control and lack of sensory feedback being major causes. Among the different types of sensory information, proprioception, e.g. information on hand aperture, is crucial to successfully perform everyday actions. Despite the many attempts in literature to restore and convey this type of feedback, much remains to be done to close the action-perception loop in prosthetic devices. Methods: With this as motivation, in this work we introduce HapPro, a wearable, non-invasive haptic device that can convey proprioceptive information for a prosthetic hand. The device was used with an under-actuated, simple to control anthropomorphic robotic hand, providing information on the level of hand aperture by mapping it to the position of a wheel that can run on the user's forearm. Tests with 43 able bodied subjects and one amputee subject were conducted in order to quantify the effectiveness of HapPro as a feedback device. Results: HapPro provided a good level of accuracy for item discrimination. Participants also reported the device to be intuitive and effective in conveying proprioceptive cues. Similar results were obtained in the proof-of-concept experiment with an amputee subject. Conclusions: Results show that HapPro is able to convey information on the opening of a prosthetic hand in a non-invasive way. Significance: Using this device for proprioceptive feedback could improve usability of myoelectric prostheses, potentially reducing abandonment and increasing quality of life for their users

Force-Aware Interface via Electromyography for Natural VR/AR Interaction

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 research towards more realistic physicality in future VR/AR.Comment: ACM Transactions on Graphics (SIGGRAPH Asia 2022