Top-down modulation of shape and roughness discrimination in active touch by covert attention

Due to limitations in perceptual processing, information relevant to momentary task goals is selected from the vast amount of available sensory information by top-down mechanisms (e.g. attention) that can increase perceptual performance. We investigated how covert attention affects perception of 3D objects in active touch. In our experiment, participants simultaneously explored the shape and roughness of two objects in sequence, and were told afterwards to compare the two objects with regard to one of the two features. To direct the focus of covert attention to the different features we manipulated the expectation of a shape or roughness judgment by varying the frequency of trials for each task (20%, 50%, 80%), then we measured discrimination thresholds. We found higher discrimination thresholds for both shape and roughness perception when the task was unexpected, compared to the conditions in which the task was expected (or both tasks were expected equally). Our results suggest that active touch perception is modulated by expectations about the task. This implies that despite fundamental differences, active and passive touch are affected by feature selective covert attention in a similar way

Deep neural network model of haptic saliency

Haptic exploration usually involves stereotypical systematic movements that are adapted to the task. Here we tested whether exploration movements are also driven by physical stimulus features. We designed haptic stimuli, whose surface relief varied locally in spatial frequency, height, orientation, and anisotropy. In Experiment 1, participants subsequently explored two stimuli in order to decide whether they were same or different. We trained a variational autoencoder to predict the spatial distribution of touch duration from the surface relief of the haptic stimuli. The model successfully predicted where participants touched the stimuli. It could also predict participants' touch distribution from the stimulus' surface relief when tested with two new groups of participants, who performed a different task (Exp. 2) or explored different stimuli (Exp. 3). We further generated a large number of virtual surface reliefs (uniformly expressing a certain combination of features) and correlated the model's responses with stimulus properties to understand the model's preferences in order to infer which stimulus features were preferentially touched by participants. Our results indicate that haptic exploratory behavior is to some extent driven by the physical features of the stimuli, with e.g. edge-like structures, vertical and horizontal patterns, and rough regions being explored in more detail

Deep neural network model of haptic saliency

Haptic exploration usually involves stereotypical systematic movements that are adapted to the task. Here we tested whether exploration movements are also driven by physical stimulus features. We designed haptic stimuli, whose surface relief varied locally in spatial frequency, height, orientation, and anisotropy. In Experiment 1, participants subsequently explored two stimuli in order to decide whether they were same or different. We trained a variational autoencoder to predict the spatial distribution of touch duration from the surface relief of the haptic stimuli. The model successfully predicted where participants touched the stimuli. It could also predict participants’ touch distribution from the stimulus’ surface relief when tested with two new groups of participants, who performed a different task (Exp. 2) or explored different stimuli (Exp. 3). We further generated a large number of virtual surface reliefs (uniformly expressing a certain combination of features) and correlated the model’s responses with stimulus properties to understand the model’s preferences in order to infer which stimulus features were preferentially touched by participants. Our results indicate that haptic exploratory behavior is to some extent driven by the physical features of the stimuli, with e.g. edge-like structures, vertical and horizontal patterns, and rough regions being explored in more detail

A NEW METHOD OF WAVELENGTH SCANNING INTERFEROMETRY FOR INSPECTING SURFACES WITH MULTI-SIDE HIGH-SLOPED FACETS

With the development of modern advanced manufacturing technologies, the requirements for ultra-precision structured surfaces are increasing rapidly for both high value-added products and scientific research. Examples of the components encompassing the structures include brightness enhancement film (BEF), optical gratings and so forth. Besides, specially designed structured surfaces, namely metamaterials can lead to specified desirable coherence, angular or spatial characteristics that the natural materials do not possess. This promising field attracts a large amount of funding and investments. However, owing to a lack of effective means of inspecting the structured surfaces, the manufacturing process is heavily reliant on the experience of fabrication operators adopting an expensive trial-and-error approach, resulting in high scrap rates up to 50-70% of the manufactured items. Therefore, overcoming this challenge becomes increasingly valuable. The thesis proposes a novel methodology to tackle this challenge by setting up an apparatus encompassing multiple measurement probes to attain the dataset for each facet of the structured surface and then blending the acquired datasets together, based on the relative location of the probes, which is achieved via the system calibration. The method relies on wavelength scanning interferometry (WSI), which can achieve areal measurement with axial resolutions approaching the nanometre without the requirement for the mechanical scanning of either the sample or optics, unlike comparable techniques such as coherence scanning interferometry (CSI). This lack of mechanical scanning opens up the possibility of using a multi-probe optics system to provide simultaneous measurement with multi adjacent fields of view. The thesis presents a proof-of-principle demonstration of a dual-probe wavelength scanning interferometry (DPWSI) system capable of measuring near-right-angle V-groove structures in a single measurement acquisition. The optical system comprises dual probes, with orthogonal measurement planes. For a given probe, a range of V-groove angles is measurable, limited by the acceptance angle of the objective lenses employed. This range can be expanded further by designing equivalent probe heads with varying angular separation. More complicated structured surfaces can be inspected by increasing the number of probes. The fringe analysis algorithms for WSI are discussed in detail, some improvements are proposed, and experimental validation is conducted. The scheme for calibrating the DPSWI system and obtaining the relative location between the probes to achieve the whole topography is implemented and presented in full. The appraisal of the DPWSI system is also carried out using a multi-step diamond-turned specimen and a sawtooth brightness enhancement film (BEF). The results showed that the proposed method could achieve the inspection of the near-right-angle V-groove structures with submicrometre scale vertical resolution and micrometre level lateral resolution

Mechanics study and application of micro-engineered smart surface

Naturally existing functional surfaces with micro-structure arose competing interests due to their potential application in engineering filed such as wetting control, optical control, micro-fluidic, tissue scaffolds, marine engineering, oil field, etc al. A patterned surface with stimuli responsive properties attracts considerable interest for its importance in advanced engineering, partly due to its reversibility, easy design and control, good compatibility and responsive behaviour to external stimuli. In this work, we have investigated various surface instabilities that enable a convenient strategy of micro-engineered structure impart reversible patterned feature to an elastic surface. We focus on the classic bi-layer system contains a stiff layer on a soft substrate that produces parallel harmonic wrinkles at uniaxial compression and ultimately develop into deep creases and fold. By introducing the microscale planar Bravais lattice holes, we guided these instabilities into various patterns to achieve an anisotropic manipulation of single liquid droplet by initialize localized surface morphologies. The Finite Element Analysis provided the fundamental theory on the surface instabilities evolution and development. The finding demonstrates considerable control over the threshold of a surface elastic instability and bi-axial switching of droplet shape that relevant to many novel applications including wearable electronic devices, bio-medical systems, micro-fluidics and optical devices

Aspheric geodesic lenses for an integrated optical spectrum analyser

Abstract available p. xiii-xi

Computational haptics : the Sandpaper system for synthesizing texture for a force-feedback display

Thesis (Ph. D.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1995.Includes bibliographical references (p. 155-180).by Margaret Diane Rezvan Minsky.Ph.D

Optically Induced Nanostructures

Nanostructuring of materials is a task at the heart of many modern disciplines in mechanical engineering, as well as optics, electronics, and the life sciences. This book includes an introduction to the relevant nonlinear optical processes associated with very short laser pulses for the generation of structures far below the classical optical diffraction limit of about 200 nanometers as well as coverage of state-of-the-art technical and biomedical applications. These applications include silicon and glass wafer processing, production of nanowires, laser transfection and cell reprogramming, optical cleaning, surface treatments of implants, nanowires, 3D nanoprinting, STED lithography, friction modification, and integrated optics. The book highlights also the use of modern femtosecond laser microscopes and nanoscopes as novel nanoprocessing tools