IEEE Transactions on Haptics最新文献

A method of providing localised haptic feedback at precise locations on the body, utilising a lightweight textile garment is presented in this short paper. The textile comprises of subtly integrated actuator yarns (HaptiYarns) which are controlled by electropneumatic circuitry. Each yarn has two functional layers, an inner porous textile layer with limited extensibility and a second, durable outer layer made from an extensible elastomer. The HaptiYarns can provide radial forces and a maximum radial displacement of 28.09 ± 0.14 mm. It was found that the intrinsic addition of graphite powder (5% by weight), during elastomer preparation, offered better resistance to layer delamination and increased the ability of the yarn to withstand higher internal air pressures by 48%. Both the graphite-filled composite and the graphite free yarns demonstrated high durability, withstanding cyclic testing of >7500 cycles while having no significant impact on the force feedback. Finally, a wearable prototype knitted textile garment is presented with eight HaptiYarns subtly integrated within it and connected to a virtual reality (VR) program providing an immersive haptic experience. These yarns offer the potential to transform everyday clothing into wearable haptic devices with potential to revolutionise healthcare, VR-based training, gaming, and entertainment sectors.

In this paper, we propose three methods to compute low-latency analog position where two of them fuse encoder and rate gyro signals. While one method is based on gyro with bias correction using encoder information, the other one is encoder-referenced combined with a resettable integrator to minimize the staircase form of encoder signals. Experiments on a one degree-of-freedom haptic simulation system have shown that a low-latency analog position with an accuracy over 98% compared to the sampled encoder signal can be obtained. The analog position signals are then utilized to produce analog viscoelastic virtual environments to assess and benchmark the proposed methods through uncoupled stability and perceived fidelity tests. The results have shown that a virtual stiffness range larger than 400% can be obtained with enhanced fidelity compared to common digital implementations.

The past decade has witnessed the development of tactile sensors, which have been increasingly considered as an essential equipment in robotics, especially the dexterous manipulation and collaborative human-robot interactions. There are two major types of tactile sensors, i.e., the vision-based and taxel-based sensors. The latter is capable of achieving lower integration complexity with existing robotic systems, but unable to provide high-resolution (HR) tactile information as that of the vision-based counterpart due to the manufacturing limitations. Therefore, we propose a novel tactile pattern super-resolution (SR) scheme for taxel-based sensors, which is a data-driven scheme enabling customized selection on the number of applied "tapping" actions to achieve improvable performance from single tapping SR (STSR) to the multi-tapping SR (MTSR). In addition, we develop a new dataset for the proposed tactile SR scheme. In order to obtain scalable resolutions (e.g. ×4, ×10, ×20, etc.) of ground-truth HR tactile patterns, we propose a novel tactile point spread function (PSF) scheme to generate HR tactile patterns by leveraging the low-resolution (LR) data gathered directly from the taxel-based sensor and the depth information of contact surfaces. This is in strong contrast to the conventional ground-truth generation approach with overlapped multi-sampling and registration strategy, which can only provide a fixed resolution. Experimental results confirm the efficiency of the proposed scheme.

Noisy vibrotactile signals transmitted during tactile explorations of an object provide precious information on the nature of its surface. Understanding the link between signal properties and how they are interpreted by the tactile sensory system remains challenging. In this paper, we investigated human perception of broadband, stationary vibrations recorded during exploration of textures and reproduced using a vibrotactile actuator. Since intensity is a well-established perceptual attribute, we here focused on the relevance of the spectral content. The stimuli were first equalized in perceived intensity and subsequently used to identify the most salient spectral features using dissimilarity estimations between pairs of successive vibration. Based on dimensionally reduced spectral representations, models of dissimilarity ratings showed that the balance between low and high frequencies was the most important cue. Formal validation of this result was achieved through a Mushra experiment, in which participants assessed the fidelity of resynthesized vibrations with various distorted frequency balances. These findings offer valuable insights into human vibrotactile perception and establish a computational framework for analyzing vibrations as humans do. Moreover, they pave the way for signal synthesis and compression based on sparse representations, holding significance for applications involving complex vibratory feedback.

This paper explores the design and experimental validation of a three-degree-of-freedom variable inertia generator. An inertia generator is a handheld haptic device that renders a prescribed inertia. In the mechanism proposed in this paper, three-dimensional torque feedback is achieved by accelerating three pairs of flywheels mounted on orthogonal axes. While the primary objective of this work is to design an inertia generator, this study also includes developing other functionalities for the device that exploit its torque generation capabilities. These include the ability to generate a predefined torque profile and to simulate a viscous environment through damping, which are both utilized to assess the device's performance. The device proved to accurately render the necessary torques for every functionality while presenting some limitations for damping and rendering an inertia smaller than the device's inherent inertia.

Electroactive textile (EAT) has the potential to apply pressure stimuli to the skin, e.g. in the form of a squeeze on the arm. To present a perceivable haptic sensation we need to know the perception threshold for such stimuli. We designed a set-up based on motorized ribbons around the arm with five different widths (range 3 - 49 mm) for psychophysical studies. We investigated the perception threshold of force pressure and ribbon reduction in two studies, using two methods (PSI and 1up/3down staircase), comparing sex, the left and right arm, the lower and upper arm, and stimulated surface area with a total of 57 participants. We found that larger stimulation surfaces require less pressure to reach the perception threshold (0.151 N per cm ² for 3 mm width, 0.00972 N per cm ² for 49 mm width on the lower arm). This indicates a spatial summation effect for these pressure stimuli. We did not find significant differences in perception threshold for the left and right arm and, the upper and lower arm. Between male and female participants we found significant differences for two conditions (10 mm and 25 mm) in Experiment 1, but we could not reproduce this in Experiment 2.

Pneumatic tactile displays dynamically customize surface morphological features with reconfigurable arrays of independently addressable actuators. However, their ability to render detailed tactile patterns or fine textures is limited by the low spatial resolution. For pneumatic tactile displays, the high-density integration of pneumatic actuators within a small space (fingertip) poses a significant challenge in terms of pneumatic circuit wiring. In contrast to the structure with a single-layer layout of pipes, we propose a multi-layered stacked microfluidic pipe structure that allows for a higher density of actuators and retains their independent actuation capabilities. Based on the proposed structure, we developed a soft microfluidic tactile display with a spatial resolution of 1.25 mm. The device consists of a 5 × 5 array of independently addressable microactuators, driven by pneumatic pressure, each of which enables independent actuation of the surface film and continuous control of the height. At a relative pressure of 1000 mbar, the actuator produced a perceptible out-of-plane deformation of 0.145 mm and a force of 17.7 mN. User studies showed that subjects can easily distinguish eight tactile patterns with 96% accuracy.

Virtual exhibits with haptic feedback offer greater flexibility in diversifying content and providing digital affordance, even at a lower cost, than physical exhibits. However, few studies addressed the value of such haptics-enabled educational systems in informal learning environments. In this study, we investigated the feasibility of a haptic exhibit as an alternative or supplement for a traditional physical exhibit in a science museum. We developed a two-degree-of-freedom cable-driven haptic device to simulate physical interactions on a large visual display. Choosing a seesaw-like physical exhibit available in a local museum, we designed and implemented a virtual lever simulation closely embodying the physics principles that the physical exhibit showcased. Then, we conducted an observational user study with children to compare the exhibit-visitor interaction behaviors, learning effects, and self-reported motivation and enjoyment between the physical and virtual exhibits. The results revealed that the visitors well-received and engaged with the haptic exhibit, instantiating its potential application in diverse learning settings. We hope that our research encourages further exploration of innovative haptic exhibits that enhance users' learning experiences across various environments.

Haptic feedback is a method to provide tactile guidance in scenarios requiring multiple senses and divided attention like aviation. Earlier tests on a flight simulator and an in-flight test using the proposed tactile guidance method have shown the need to study its learning process. In this study, twelve participants completed two tactile guidance tasks without visual feedback across twelve sessions to analyze the learning effect. The paper shows an improvement between sessions in guidance accuracy, response time, and self-assessed workload. On the other hand, reaction delay is not affected by the training. The percentage improvement between the initial and trained skills reached 30 % in guidance accuracy performance.

For human sensory processing, cluttered real-world environments where signals from multiple objects or events overlap are challenging. A cognitive function useful in such situations is an attentional selection of one signal from others based on the difference in bound feature. For instance, one can visually select a specific orientation if it is uniquely colored. However, here we show that unlike vision, touch is very poor at feature-based signal selection. We presented two-orthogonal line segments with different vibration textures to a fingertip. Though observers were markedly sensitive to each feature, they were generally unable to identify the orientation bound with a specific texture when the segments were presented simultaneously or in rapid alternation. A similar failure was observed for a direction judgment task. These results demonstrate a general cognitive limitation of touch, highlighting its unique bias to integrate multiple signals into a global event rather than segment them into separate events.