12,325 research outputs found
Mid-air haptic rendering of 2D geometric shapes with a dynamic tactile pointer
An important challenge that affects ultrasonic midair haptics, in contrast to physical touch, is that we lose certain exploratory procedures such as contour following. This makes the task of perceiving geometric properties and shape identification more difficult. Meanwhile, the growing interest in mid-air haptics and their application to various new areas requires an improved understanding of how we perceive specific haptic stimuli, such as icons and control dials in mid-air. We address this challenge
by investigating static and dynamic methods of displaying 2D geometric shapes in mid-air. We display a circle, a square, and a triangle, in either a static or dynamic condition, using ultrasonic mid-air haptics. In the static condition, the shapes are presented as a full outline in mid-air, while in the dynamic condition, a tactile pointer is moved around the perimeter of the shapes. We measure participants’ accuracy and confidence of identifying
shapes in two controlled experiments (n1 = 34, n2 = 25). Results reveal that in the dynamic condition people recognise shapes significantly more accurately, and with higher confidence. We also find that representing polygons as a set of individually drawn haptic strokes, with a short pause at the corners, drastically enhances shape recognition accuracy. Our research supports the design of mid-air haptic user interfaces in application scenarios
such as in-car interactions or assistive technology in education
A Review of Smart Materials in Tactile Actuators for Information Delivery
As the largest organ in the human body, the skin provides the important
sensory channel for humans to receive external stimulations based on touch. By
the information perceived through touch, people can feel and guess the
properties of objects, like weight, temperature, textures, and motion, etc. In
fact, those properties are nerve stimuli to our brain received by different
kinds of receptors in the skin. Mechanical, electrical, and thermal stimuli can
stimulate these receptors and cause different information to be conveyed
through the nerves. Technologies for actuators to provide mechanical,
electrical or thermal stimuli have been developed. These include static or
vibrational actuation, electrostatic stimulation, focused ultrasound, and more.
Smart materials, such as piezoelectric materials, carbon nanotubes, and shape
memory alloys, play important roles in providing actuation for tactile
sensation. This paper aims to review the background biological knowledge of
human tactile sensing, to give an understanding of how we sense and interact
with the world through the sense of touch, as well as the conventional and
state-of-the-art technologies of tactile actuators for tactile feedback
delivery
Tactons: structured tactile messages for non-visual information display
Tactile displays are now becoming available in a form that can be easily used in a user interface. This paper describes a new form of tactile output. Tactons, or tactile icons, are structured, abstract messages that can be used to communicate messages non-visually. A range of different parameters can be used for Tacton construction including: frequency, amplitude and duration of a tactile pulse, plus other parameters such as rhythm and location. Tactons have the potential to improve interaction in a range of different areas, particularly where the visual display is overloaded, limited in size or not available, such as interfaces for blind people or in mobile and wearable devices. This paper describes Tactons, the parameters used to construct them and some possible ways to design them. Examples of where Tactons might prove useful in user interfaces are given
Multi-Modal Human-Machine Communication for Instructing Robot Grasping Tasks
A major challenge for the realization of intelligent robots is to supply them
with cognitive abilities in order to allow ordinary users to program them
easily and intuitively. One way of such programming is teaching work tasks by
interactive demonstration. To make this effective and convenient for the user,
the machine must be capable to establish a common focus of attention and be
able to use and integrate spoken instructions, visual perceptions, and
non-verbal clues like gestural commands. We report progress in building a
hybrid architecture that combines statistical methods, neural networks, and
finite state machines into an integrated system for instructing grasping tasks
by man-machine interaction. The system combines the GRAVIS-robot for visual
attention and gestural instruction with an intelligent interface for speech
recognition and linguistic interpretation, and an modality fusion module to
allow multi-modal task-oriented man-machine communication with respect to
dextrous robot manipulation of objects.Comment: 7 pages, 8 figure
Connecting Look and Feel: Associating the visual and tactile properties of physical materials
For machines to interact with the physical world, they must understand the
physical properties of objects and materials they encounter. We use fabrics as
an example of a deformable material with a rich set of mechanical properties. A
thin flexible fabric, when draped, tends to look different from a heavy stiff
fabric. It also feels different when touched. Using a collection of 118 fabric
sample, we captured color and depth images of draped fabrics along with tactile
data from a high resolution touch sensor. We then sought to associate the
information from vision and touch by jointly training CNNs across the three
modalities. Through the CNN, each input, regardless of the modality, generates
an embedding vector that records the fabric's physical property. By comparing
the embeddings, our system is able to look at a fabric image and predict how it
will feel, and vice versa. We also show that a system jointly trained on vision
and touch data can outperform a similar system trained only on visual data when
tested purely with visual inputs
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