Incompressible Squeeze-Film Levitation

Transverse vibrations can induce the non-linear compression of a thin film of air to levitate objects, via the squeeze film effect. This phenomenon is well captured by the Reynolds' lubrication theory, however, the same theory fails to describe this levitation when the fluid is incompressible. In this case, the computation predicts no steady-state levitation, contradicting the documented experimental evidence. In this letter, we uncover the main source of the time-averaged pressure asymmetry in the incompressible fluid thin film, leading the levitation phenomenon to exist. Furthermore, we reveal the physical law governing the steady-state levitation height, which we confirm experimentally

Rapid manufacturing of color-based hemispherical soft tactile fingertips

Tactile sensing can provide access to information about the contact (i.e. slippage, surface feature, friction), which is out of reach of vision but crucial for manipulation. To access this information, a dense measurement of the deformation of soft fingertips is necessary. Recently, tactile sensors that rely on a camera looking at a deformable membrane have demonstrated that a dense measurement of the contact is possible. However, their manufacturing can be time-consuming and labor-intensive. Here, we show a new design method that uses multi-color additive manufacturing and silicone casting to efficiently manufacture soft marker-based tactile sensors that are able to capture with high-resolution the three-dimensional deformation field at the interface. Each marker is composed of two superimposed color filters. The subtractive color mixing encodes the normal deformation of the membrane, and the lateral deformation is found by centroid detection. With this manufacturing method, we can reach a density of 400 markers on a 21 mm radius hemisphere, allowing for regular and dense measurement of the deformation. We calibrated and validated the approach by finding the curvature of objects with a threefold increase in accuracy as compared to previous implementations. The results demonstrate a simple yet effective approach to manufacturing artificial fingertips for capturing a rich image of the tactile interaction at the location of contact

Mechanically-Inflatable Bio-Inspired Locomotion for Robotic Pipeline Inspection

Pipelines, vital for fluid transport, pose an important yet challenging inspection task, particularly in small, flexible biological systems, that robots have yet to master. In this study, we explored the development of an innovative robot inspired by the ovipositor of parasitic wasps to navigate and inspect pipelines. The robot features a flexible locomotion system that adapts to different tube sizes and shapes through a mechanical inflation technique. The flexible locomotion system employs a reciprocating motion, in which groups of three sliders extend and retract in a cyclic fashion. In a proof-of-principle experiment, the robot locomotion efficiency demonstrated positive linear correlation (r=0.6434) with the diameter ratio (ratio of robot diameter to tube diameter). The robot showcased a remarkable ability to traverse tubes of different sizes, shapes and payloads with an average of (70%) locomotion efficiency across all testing conditions, at varying diameter ratios (0.7-1.5). Furthermore, the mechanical inflation mechanism displayed substantial load-carrying capacity, producing considerable holding force of (13 N), equivalent to carrying a payload of approximately (5.8 Kg) inclusive the robot weight. This novel soft robotic system shows promise for inspection and navigation within tubular confined spaces, particularly in scenarios requiring adaptability to different tube shapes, sizes, and load-carrying capacities. This novel design serves as a foundation for a new class of pipeline inspection robots that exhibit versatility across various pipeline environments, potentially including biological systems.Comment: Accepted paper for RoboSoft 202

Attention-based Robot Learning of Haptic Interaction

Moringen A, Fleer S, Walck G, Ritter H. Attention-based Robot Learning of Haptic Interaction. In: Nisky I, Hartcher-O’Brien J, Wiertlewski M, Smeets J, eds. Haptics: Science, Technology, Applications. 12th International Conference, EuroHaptics 2020, Leiden, The Netherlands, September 6–9, 2020, Proceedings. Lecture Notes in Computer Science. Vol 12272. Cham: Springer; 2020: 462-470.Haptic interaction involved in almost any physical interaction with the environment performed by humans is a highly sophisticated and to a large extent a computationally unmodelled process. Unlike humans, who seamlessly handle a complex mixture of haptic features and profit from their integration over space and time, even the most advanced robots are strongly constrained in performing contact-rich interaction tasks. In this work we approach the described problem by demonstrating the success of our online haptic interaction learning approach on an example task: haptic identification of four unknown objects. Building upon our previous work performed with a floating haptic sensor array, here we show functionality of our approach within a fully-fledged robot simulation. To this end, we utilize the haptic attention model (HAM), a meta-controller neural network architecture trained with reinforcement learning. HAM is able to learn to optimally parameterize a sequence of so-called haptic glances, primitive actions of haptic control derived from elementary human haptic interaction. By coupling a simulated KUKA robot arm with the haptic attention model, we pursue to mimic the functionality of a finger. Our modeling strategy allowed us to arrive at a tactile reinforcement learning architecture and characterize some of its advantages. Owing to a rudimentary experimental setting and an easy acquisition of simulated data, we believe our approach to be particularly useful for both time-efficient robot training and a flexible algorithm prototyping

On the 1/f noise and noninteger harmonic decay of the interaction of a finger sliding on flat and sinusoidal surfaces

Intelligents et de Robotique

Physical and behavioral comparison of haptic touchscreens quality

Touchscreens equipped with friction modulation can provide rich tactile feedback to their users. To date, there are no standard metrics to properly quantify the benefit brought by haptic feedback. The definition of such metrics is not straightforward since friction modulation technologies can be achieved by either ultrasonic waves or with electroadhesion. In addition, the output depends strongly on the user, both because of the mechanical behavior of the fingertip and personal tactile somatosensory capabilities. This paper proposes a method to evaluate and compare the performance of haptic tablets on an objective scale. The method first defines multiple metrics using physical measurements of friction and latency. The comparison is completed with metrics derived from information theory and based on pointing tasks performed by users. We evaluated the comparison method with two haptic devices, one based on ultrasonic friction modulation and the other based on electroadhesion. This work paves the way toward the definitions of standard specifications for haptic tablets, to establish benchmarks and guidelines for improving surface haptic devices

Physical and behavioral comparison of haptic touchscreens

Touchscreens equipped with friction modulation can provide rich tactile feedback to their users. To date, there are no standard metrics to properly quantify the benefit brought byhaptic feedback on touchscreen usability. The definition of such metrics is not straightforward since friction modulation technologies can be achieved by either ultrasonic waves or with electroadhesion. In addition, the output depends strongly on the user, both because of the mechanical behavior of the fingertip and personal tactile somatosensorycapabilities. We investigate here a method to evaluate and compare the performance of haptic tablets on an objective scale. The method first defines some metrics using physicalmeasurements of friction and latency. The comparison is completed with metrics based on pointing tasks performed by users. We evaluated the comparison method with two hapticdevices, one based on ultrasonic friction modulation (Tpad) and the other based on electroadhesion (Tanvas)

Preface

This open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility